Pipeline run
06a2fdaa-518e-402e-9258-c8cd58ecd5b0
Client output enrichment
v2 Skill cluster · Nature of work · AI index · Tech stack maturity · Evidence · KRA descriptionvocab breakdown (legacy)
Signals
Post-classification
Captured for admin review
1 POST /skills/extract-from-jd
2 POST /skills/extract-details
3 POST /skills/final-role-output
ML Engineer
domain · AI / ML CASE DOMAINslug: ml-engineer · id: 3 · source: db
Domain=AI / ML; The JD centers on building and training Python-based OCR and AI/ML solutions, which aligns best with ML Engineer rather than a pure CV or MLOps role.
Matched skills
Matched dimensions
Matched KRAs
Resolution:
in_db
— role exists in library; skill↔dim and role↔dim links saved when applicable.
Job description
Skills: Python programming, AI/ML, OCR, Devops, NLP, docker, Kindly find the company website: https://www.microvistatech.com/ Job Description: Python Developer (3+ Years Experience with OCR and AI/ML Expertise) Position Overview We are seeking a highly skilled Python Developer with over 3 years of experience, specializing in Optical Character Recognition (OCR) and Artificial Intelligence/Machine Learning (AI/ML) technologies. The ideal candidate will be responsible for designing, implementing, and optimizing AI-driven solutions and OCR systems to meet the organization's technical and business requirements. Key Responsibilities Python Development: Develop, test, and maintain scalable Python applications and scripts. Optimize existing codebases for performance, readability, and maintainability. OCR Implementation Design and integrate OCR solutions using tools like Tesseract, Google Vision API, or AWS Textract. Enhance OCR models with preprocessing techniques such as noise removal, binarization, and image enhancement. Handle extraction, parsing, and validation of structured and unstructured data from scanned documents. AI/ML Development Develop and train machine learning models using frameworks like TensorFlow, PyTorch, or Scikit-learn. Implement Natural Language Processing (NLP) for document classification and data extraction. Continuously fine-tune AI models to improve accuracy and efficiency. Integration And Deployment Deploy AI/ML solutions into production environments. Ensure seamless integration with existing systems and applications. Data Management Work with large datasets, including data preprocessing, augmentation, and analysis. Collaborate with data engineers to design pipelines for continuous data processing. Collaboration Work closely with cross-functional teams, including product managers, UI/UX designers, and data scientists. Translate business requirements into technical specifications and solutions. Documentation And Support Document code, processes, and best practices. Provide technical support and troubleshooting for deployed systems. Qualifications And Skills Educational Background: Bachelors or Masters degree in Computer Science, Engineering, or related fields. Experience 3+ years of professional experience in Python development. Proven experience with OCR tools and frameworks (e.g., Tesseract, OpenCV, ABBYY, Keras-OCR). Strong understanding of AI/ML concepts, algorithms, and frameworks. Technical Skills Hands-on experience with machine learning frameworks (TensorFlow, PyTorch, or Scikit-learn). Proficiency in image processing libraries (e.g., OpenCV, PIL). Experience in NLP libraries like SpaCy or NLTK is a plus. Knowledge of cloud-based AI/ML services (AWS, Google Cloud, Azure). Soft Skills Strong problem-solving and analytical skills. Excellent verbal and written communication abilities. Ability to work both independently and collaboratively in a team environment. Preferred Skills Knowledge of DevOps practices and containerization (Docker, Kubernetes). Familiarity with databases (SQL and NoSQL). Experience in API development and integration.
Skills from this JD
Each row merges API 1 extraction, API 2 library match / v3 orchestration (dimensions + locked dims), and API 3 persistence tags.
Aliases — catalog
- Python (CANONICAL) primary
- Python 2 (VERSION)
- Python 2.x (VERSION)
- Python 3 (VERSION)
- Python 3.10 (VERSION)
- Python 3.11 (VERSION)
- Python 3.12 (VERSION)
- Python 3.x (VERSION)
- py (VERSION)
- py2 (VERSION)
- py3 (VERSION)
- python 3 (VERSION)
- python 3.x (VERSION)
- python2 (VERSION)
- python3 (VERSION)
- python3.x (VERSION)
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Language
- Sub-category
- Programming Language
- Vendor
- PSF
- License
- mit
- Year introduced
- 1991
- Confidence
- 0.99
- Version strategy
- SEPARATE_ENTITY
- Version tag
- 3
Maturity reasoning: Python appears in a very high volume of job descriptions across data, backend, automation, and ML roles, and remains a default hiring-pipeline language on major job boards and tech stacks.
Skill profile (library / DB)
- Skill nature
- LANGUAGE
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 6
- Sub-category id
- 96
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Cloud Security Scripting & DSL Languages Catalog dimension db id 248
Library dimension (catalog)
Roles linked in library: Cloud Security Engineer
-
Programming Languages Catalog dimension db id 1
Library dimension (catalog)
Roles linked in library: Backend Developer, Fullstack Developer
-
Programming Languages and Scripting Catalog dimension db id 59
Library dimension (catalog)
Roles linked in library: Cyber Security Engineer
-
Programming Languages for Data Work Catalog dimension db id 21
Library dimension (catalog)
Roles linked in library: Data Engineer
-
Programming Languages for ML Systems Catalog dimension db id 39
Library dimension (catalog)
Roles linked in library: ML Engineer, MLOps Engineer
-
Programming Languages for XR Catalog dimension db id 97
Library dimension (catalog)
Roles linked in library: AR/VR Engineer
-
Python Programming Catalog dimension db id 290
Library dimension (catalog)
Roles linked in library: Python Backend Developer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Cloud Security Scripting & DSL Languages
cloud-security-scripting-dsl-languages
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Programming Languages
programming-languages
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Programming Languages and Scripting
programming-languages-and-scripting
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Programming Languages for Data Work
programming-languages-for-data-work
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Programming Languages for ML Systems
programming-languages-for-ml-systems
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved |
|
Programming Languages for XR
programming-languages-for-xr
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Python Programming
python-programming
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Aliases — catalog
- OCR (CANONICAL)
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Concept
- Sub-category
- Optical Character Recognition
- Confidence
- 0.93
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: OCR is broadly used in enterprise document workflows and appears frequently in job postings for automation, IDP, and computer vision roles; cloud vendors also offer mature OCR APIs.
Skill profile (library / DB)
- Skill nature
- CONCEPT
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 2
- Sub-category id
- 1184
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
React Frontend Development Catalog dimension db id 96
Library dimension (catalog)
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
React Frontend Development
d_init_01
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Aliases — catalog
- Artificial Intelligence (CANONICAL)
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Concept
- Sub-category
- Artificial Intelligence
- Confidence
- 0.98
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: AI appears in a large and growing share of job descriptions across software, data, and product roles, and major vendors (Microsoft, Google, AWS) have standardized AI offerings, signaling broad market adoption.
Skill profile (library / DB)
- Skill nature
- CONCEPT
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 2
- Sub-category id
- 1020
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
React Frontend Development Catalog dimension db id 96
Library dimension (catalog)
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
React Frontend Development
d_init_01
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Aliases — catalog
- Machine Learning (CANONICAL)
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Concept
- Sub-category
- Machine Learning
- Confidence
- 0.98
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Machine Learning appears in large volumes of job descriptions across data, product, and platform roles, and major cloud vendors (AWS, Google Cloud, Azure) offer dedicated ML services and certifications, indicating broad adoption.
Skill profile (library / DB)
- Skill nature
- CONCEPT
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 2
- Sub-category id
- 1024
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
AI Governance and Model Security Catalog dimension db id 50
Library dimension (catalog)
Roles linked in library: AI Engineer, ML Engineer, MLOps Engineer
-
React Frontend Development Catalog dimension db id 96
Library dimension (catalog)
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
AI Governance and Model Security
ai-governance-and-model-security
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved |
|
React Frontend Development
d_init_01
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Optical Character Recognition
- Sub-category
- general
- Skill nature
- TOOL
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Cloud Services
- Sub-category
- general
- Skill nature
- PLATFORM
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Cloud Services
- Sub-category
- general
- Skill nature
- PLATFORM
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Aliases — catalog
- TensorFlow (CANONICAL) primary
- TF1 (VERSION)
- TF2 (VERSION)
- TensorFlow 1 (VERSION)
- TensorFlow 1.x (VERSION)
- TensorFlow 2 (VERSION)
- TensorFlow 2.x (VERSION)
- tensorflow 1 (VERSION)
- tensorflow 1.x (VERSION)
- tensorflow 2 (VERSION)
- tensorflow 2.x (VERSION)
- tensorflow v1 (VERSION)
- tensorflow v2 (VERSION)
- tf (VERSION)
- tf1 (VERSION)
- tf2 (VERSION)
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Library
- Sub-category
- Machine Learning Library
- Vendor
- License
- apache_2
- Year introduced
- 2015
- Confidence
- 0.90
- Version strategy
- SEPARATE_ENTITY
- Version tag
- 2.x
Maturity reasoning: TensorFlow appears in many ML/AI job descriptions and remains a standard production framework, with strong GitHub activity and broad vendor support from Google and cloud platforms.
Skill profile (library / DB)
- Skill nature
- LIBRARY
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 7
- Sub-category id
- 156
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
ML Frameworks and Libraries Catalog dimension db id 40
Library dimension (catalog)
Roles linked in library: ML Engineer, MLOps Engineer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
ML Frameworks and Libraries
ml-frameworks-and-libraries
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved |
Aliases — catalog
- PyTorch (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Library
- Sub-category
- Machine Learning Library
- Vendor
- Meta
- License
- bsd
- Year introduced
- 2016
- Confidence
- 0.90
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: PyTorch appears in a large volume of ML/AI job descriptions and is a standard framework in research and production, alongside TensorFlow and CUDA ecosystems.
Skill profile (library / DB)
- Skill nature
- LIBRARY
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 7
- Sub-category id
- 156
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
ML Frameworks and Libraries Catalog dimension db id 40
Library dimension (catalog)
Roles linked in library: ML Engineer, MLOps Engineer
-
Model Fine-Tuning & Adaptation Catalog dimension db id 212
Library dimension (catalog)
Roles linked in library: AI Engineer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
ML Frameworks and Libraries
ml-frameworks-and-libraries
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved |
|
Model Fine-Tuning & Adaptation
model-fine-tuning-adaptation
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Aliases — catalog
- scikit-learn (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Library
- Sub-category
- Machine Learning Library
- Vendor
- scikit-learn developers
- License
- bsd
- Year introduced
- 2007
- Confidence
- 0.95
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Commonly listed in ML/data science job descriptions and widely used in production Python ML stacks; no vendor sunset or replacement signal, and GitHub activity remains strong.
Skill profile (library / DB)
- Skill nature
- LIBRARY
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 7
- Sub-category id
- 156
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
ML Frameworks and Libraries Catalog dimension db id 40
Library dimension (catalog)
Roles linked in library: ML Engineer, MLOps Engineer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
ML Frameworks and Libraries
ml-frameworks-and-libraries
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved |
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Concepts
- Sub-category
- general
- Skill nature
- CONCEPT
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Version strategy
- UNVERSIONED
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Computer Vision Libraries
- Sub-category
- general
- Skill nature
- TOOL
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Image Processing Libraries
- Sub-category
- general
- Skill nature
- TOOL
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Natural Language Processing Libraries
- Sub-category
- general
- Skill nature
- TOOL
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Natural Language Processing Libraries
- Sub-category
- general
- Skill nature
- TOOL
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Aliases — catalog
- AWS (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Platform
- Sub-category
- Cloud Platform
- Vendor
- Amazon
- License
- other_open
- Year introduced
- 2006
- Confidence
- 0.99
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: AWS is a hiring-pipeline staple: it appears in a large share of cloud/DevOps job descriptions and dominates public cloud market share, with broad certification and vendor ecosystem support.
Skill profile (library / DB)
- Skill nature
- PLATFORM
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 9
- Sub-category id
- 46
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Cloud Platforms Catalog dimension db id 20
Library dimension (catalog)
Roles linked in library: .NET Backend Developer, Backend Developer, Cyber Security Engineer, Data Engineer, DevOps Engineer, Fullstack Developer, Go Backend Developer, Java Backend Developer, Kotlin Backend Developer, ML Engineer, MLOps Engineer, Node.js Backend Developer, Python Backend Developer, Scala Backend Developer
-
Cloud Platforms for AI Deployment Catalog dimension db id 211
Library dimension (catalog)
Roles linked in library: AI Engineer
-
Cloud Provider Platforms Catalog dimension db id 131
Library dimension (catalog)
Roles linked in library: Cloud Architect, Cloud Security Engineer
-
Cloud Security Posture Tools Catalog dimension db id 64
Library dimension (catalog)
Roles linked in library: Cloud Security Engineer, Cyber Security Engineer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Cloud Platforms
cloud-platforms
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved |
|
Cloud Platforms for AI Deployment
cloud-platforms-for-ai-deployment
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Cloud Provider Platforms
cloud-provider-platforms
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Cloud Security Posture Tools
cloud-security-posture-tools
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Aliases — catalog
- Google Cloud Platform (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Platform
- Sub-category
- Cloud Platform
- Vendor
- License
- other_open
- Year introduced
- 2008
- Confidence
- 0.99
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: GCP appears in many cloud-engineering job descriptions alongside AWS/Azure, and Google continues expanding managed services and certifications, indicating broad hiring demand rather than niche use.
Skill profile (library / DB)
- Skill nature
- PLATFORM
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 9
- Sub-category id
- 46
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Cloud & Hosting Providers Catalog dimension db id 414
Library dimension (catalog)
Roles linked in library: PHP Backend Developer
-
Cloud Provider Platforms Catalog dimension db id 131
Library dimension (catalog)
Roles linked in library: Cloud Architect, Cloud Security Engineer
-
Cloud Security Posture Tools Catalog dimension db id 64
Library dimension (catalog)
Roles linked in library: Cloud Security Engineer, Cyber Security Engineer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Cloud & Hosting Providers
cloud-hosting-providers
|
— | — |
Skipped — no persistable v3 meta for new skill
skill_not_in_db_v3_proposed
|
|
Cloud Provider Platforms
cloud-provider-platforms
|
— | — |
Skipped — no persistable v3 meta for new skill
skill_not_in_db_v3_proposed
|
|
Cloud Security Posture Tools
cloud-security-posture-tools
|
— | — |
Skipped — no persistable v3 meta for new skill
skill_not_in_db_v3_proposed
|
Aliases — catalog
- Azure (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Platform
- Sub-category
- Cloud Platform
- Vendor
- Microsoft
- License
- proprietary
- Year introduced
- 2010
- Confidence
- 0.99
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Azure is broadly adopted and frequently appears in cloud/platform job descriptions alongside AWS and GCP; Microsoft’s ongoing enterprise investment and Azure certification demand signal strong hiring-pipeline relevance.
Skill profile (library / DB)
- Skill nature
- PLATFORM
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 9
- Sub-category id
- 46
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Cloud Platforms Catalog dimension db id 20
Library dimension (catalog)
Roles linked in library: .NET Backend Developer, Backend Developer, Cyber Security Engineer, Data Engineer, DevOps Engineer, Fullstack Developer, Go Backend Developer, Java Backend Developer, Kotlin Backend Developer, ML Engineer, MLOps Engineer, Node.js Backend Developer, Python Backend Developer, Scala Backend Developer
-
Cloud Platforms & Managed Services Catalog dimension db id 221
Library dimension (catalog)
Roles linked in library: Fullstack Developer, Go Backend Developer, Node.js Backend Developer
-
Cloud Platforms for AI Deployment Catalog dimension db id 211
Library dimension (catalog)
Roles linked in library: AI Engineer
-
Cloud Provider Platforms Catalog dimension db id 131
Library dimension (catalog)
Roles linked in library: Cloud Architect, Cloud Security Engineer
-
Cloud Security Posture Tools Catalog dimension db id 64
Library dimension (catalog)
Roles linked in library: Cloud Security Engineer, Cyber Security Engineer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Cloud Platforms
cloud-platforms
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved |
|
Cloud Platforms & Managed Services
cloud-platforms-managed-services
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Cloud Platforms for AI Deployment
cloud-platforms-for-ai-deployment
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Cloud Provider Platforms
cloud-provider-platforms
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Cloud Security Posture Tools
cloud-security-posture-tools
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Aliases — catalog
- DevOps (CANONICAL)
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Methodology
- Sub-category
- Devops Methodology
- Confidence
- 0.97
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: DevOps appears in a large share of software and platform engineering job descriptions, often alongside CI/CD, Kubernetes, and cloud tooling; it is a standard hiring-pipeline keyword rather than a niche specialty.
Skill profile (library / DB)
- Skill nature
- METHODOLOGY
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 8
- Sub-category id
- 922
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
CI/CD Pipeline Platforms Catalog dimension db id 150
Library dimension (catalog)
Roles linked in library: DevOps Engineer
-
Deployment and Release Patterns Catalog dimension db id 140
Library dimension (catalog)
Roles linked in library: Cloud Architect
-
Infrastructure as Code Catalog dimension db id 132
Library dimension (catalog)
Roles linked in library: Cloud Architect, DevOps Engineer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
CI/CD Pipeline Platforms
ci-cd-pipeline-platforms
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Deployment and Release Patterns
deployment-and-release-patterns
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Infrastructure as Code
infrastructure-as-code
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Aliases — catalog
- Docker (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Tool
- Sub-category
- Containerization Tool
- Vendor
- Docker, Inc.
- License
- apache_2
- Year introduced
- 2013
- Confidence
- 0.98
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Docker is a hiring-pipeline staple: it appears in many DevOps, backend, and platform JDs, and remains a standard containerization tool alongside Kubernetes in production stacks.
Skill profile (library / DB)
- Skill nature
- TOOL
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 13
- Sub-category id
- 63
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Containerization and Image Builds Catalog dimension db id 152
Library dimension (catalog)
Roles linked in library: DevOps Engineer
-
Deployment and Cloud Platforms Catalog dimension db id 418
Library dimension (catalog)
Roles linked in library: Ruby Backend Developer
-
Deployment and Runtime Configuration Catalog dimension db id 13
Library dimension (catalog)
Roles linked in library: .NET Backend Developer, Backend Developer, Go Backend Developer, PHP Backend Developer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Containerization and Image Builds
containerization-and-image-builds
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Deployment and Cloud Platforms
deployment-and-cloud-platforms
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Deployment and Runtime Configuration
deployment-and-runtime-configuration
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Aliases — catalog
- Kubernetes (CANONICAL) primary
- Kubernetes 1.0+ (VERSION)
- Kubernetes 1.x (VERSION)
- Kubernetes v1 (VERSION)
- k8s (VERSION)
- kubernetes 1.x (VERSION)
- kubernetes latest (VERSION)
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Platform
- Sub-category
- Container Orchestration Platform
- Vendor
- Cloud Native Computing Foundation
- License
- apache_2
- Year introduced
- 2014
- Confidence
- 0.90
- Version strategy
- SEPARATE_ENTITY
- Version tag
- 1.30
Maturity reasoning: Broadly adopted in cloud-native stacks; Kubernetes appears in a large share of DevOps/SRE job descriptions and is the default orchestration platform across major cloud vendors.
Skill profile (library / DB)
- Skill nature
- PLATFORM
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 9
- Sub-category id
- 557
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Container Orchestration Platforms Catalog dimension db id 134
Library dimension (catalog)
Roles linked in library: Cloud Architect, DevOps Engineer
-
Kubernetes for ML Workloads Catalog dimension db id 47
Library dimension (catalog)
Roles linked in library: ML Engineer, MLOps Engineer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Container Orchestration Platforms
container-orchestration-platforms
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Kubernetes for ML Workloads
kubernetes-for-ml-workloads
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved |
Aliases — catalog
- SQL (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Language
- Sub-category
- Query Language
- Vendor
- ANSI
- License
- unknown
- Year introduced
- 1974
- Confidence
- 0.99
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: SQL appears in a large share of data, backend, and analytics job descriptions and remains the default query language for PostgreSQL, MySQL, and cloud warehouses like Snowflake/BigQuery.
Skill profile (library / DB)
- Skill nature
- LANGUAGE
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 6
- Sub-category id
- 97
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Pega Programming Languages & DSLs Catalog dimension db id 267
Library dimension (catalog)
Roles linked in library: Pega Developer
-
Programming Languages for Data Work Catalog dimension db id 21
Library dimension (catalog)
Roles linked in library: Data Engineer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Pega Programming Languages & DSLs
pega-programming-languages-dsls
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Programming Languages for Data Work
programming-languages-for-data-work
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Aliases — catalog
- NoSQL (CANONICAL)
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Concept
- Sub-category
- Database Paradigm
- Confidence
- 0.93
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: NoSQL is broadly listed in job descriptions across backend/data roles, with MongoDB, DynamoDB, and Cassandra appearing as common market signals; it remains a hiring-pipeline staple rather than a niche or sunset tech.
Skill profile (library / DB)
- Skill nature
- CONCEPT
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 2
- Sub-category id
- 1019
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
NoSQL Databases Catalog dimension db id 19
Library dimension (catalog)
Roles linked in library: Backend Developer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
NoSQL Databases
nosql-databases
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Development Practices
- Sub-category
- general
- Skill nature
- PRACTICE
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Aliases — catalog
- API Integration (CANONICAL)
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Concept
- Sub-category
- Api Integration
- Confidence
- 0.90
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: API integration appears in a large share of software engineering JDs and is a standard requirement across backend, frontend, and platform roles; it is a core hiring-pipeline skill rather than a niche tool.
Skill profile (library / DB)
- Skill nature
- CONCEPT
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 2
- Sub-category id
- 1210
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
API Integration and Data Fetching Catalog dimension db id 127
Library dimension (catalog)
Roles linked in library: Angular Frontend Developer, Frontend Developer, Fullstack Developer, React Frontend Developer, Svelte Frontend Developer, Vue Frontend Developer, Web Developer
-
Cross-Platform App Languages Catalog dimension db id 167
Library dimension (catalog)
Roles linked in library: Hybrid Mobile Developer
-
Networking and API Integration Catalog dimension db id 84
Library dimension (catalog)
Roles linked in library: Android Developer, Hybrid Mobile Developer, Native Mobile Developer, iOS Developer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
API Integration and Data Fetching
api-integration-and-data-fetching
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Cross-Platform App Languages
cross-platform-app-languages
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Networking and API Integration
networking-and-api-integration
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
All API 3 persistence rows
Same grid as the skill-extractor “Persistence items” table: one row per (skill × dimension) work item.
| Skill | Tag | Dimension | Skill↔dim | Role↔dim | Outcome | Notes |
|---|---|---|---|---|---|---|
| Python | in_db |
Cloud Security Scripting & DSL Languages
cloud-security-scripting-dsl-languages
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Python | in_db |
Programming Languages
programming-languages
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Python | in_db |
Programming Languages and Scripting
programming-languages-and-scripting
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Python | in_db |
Programming Languages for Data Work
programming-languages-for-data-work
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Python | in_db |
Programming Languages for ML Systems
programming-languages-for-ml-systems
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved | |
| Python | in_db |
Programming Languages for XR
programming-languages-for-xr
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Python | in_db |
Python Programming
python-programming
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| OCR | in_db |
React Frontend Development
d_init_01
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Artificial Intelligence | in_db |
React Frontend Development
d_init_01
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Machine Learning | in_db |
AI Governance and Model Security
ai-governance-and-model-security
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved | |
| Machine Learning | in_db |
React Frontend Development
d_init_01
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| TensorFlow | in_db |
ML Frameworks and Libraries
ml-frameworks-and-libraries
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved | |
| PyTorch | in_db |
ML Frameworks and Libraries
ml-frameworks-and-libraries
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved | |
| PyTorch | in_db |
Model Fine-Tuning & Adaptation
model-fine-tuning-adaptation
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Scikit-learn | in_db |
ML Frameworks and Libraries
ml-frameworks-and-libraries
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved | |
| AWS | in_db |
Cloud Platforms
cloud-platforms
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved | |
| AWS | in_db |
Cloud Platforms for AI Deployment
cloud-platforms-for-ai-deployment
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| AWS | in_db |
Cloud Provider Platforms
cloud-provider-platforms
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| AWS | in_db |
Cloud Security Posture Tools
cloud-security-posture-tools
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Google Cloud | new |
Cloud & Hosting Providers
cloud-hosting-providers
|
— | — | Skipped — no persistable v3 meta for new skill | skill_not_in_db_v3_proposed |
| Google Cloud | new |
Cloud Provider Platforms
cloud-provider-platforms
|
— | — | Skipped — no persistable v3 meta for new skill | skill_not_in_db_v3_proposed |
| Google Cloud | new |
Cloud Security Posture Tools
cloud-security-posture-tools
|
— | — | Skipped — no persistable v3 meta for new skill | skill_not_in_db_v3_proposed |
| Azure | in_db |
Cloud Platforms
cloud-platforms
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved | |
| Azure | in_db |
Cloud Platforms & Managed Services
cloud-platforms-managed-services
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Azure | in_db |
Cloud Platforms for AI Deployment
cloud-platforms-for-ai-deployment
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Azure | in_db |
Cloud Provider Platforms
cloud-provider-platforms
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Azure | in_db |
Cloud Security Posture Tools
cloud-security-posture-tools
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| DevOps | in_db |
CI/CD Pipeline Platforms
ci-cd-pipeline-platforms
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| DevOps | in_db |
Deployment and Release Patterns
deployment-and-release-patterns
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| DevOps | in_db |
Infrastructure as Code
infrastructure-as-code
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Docker | in_db |
Containerization and Image Builds
containerization-and-image-builds
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Docker | in_db |
Deployment and Cloud Platforms
deployment-and-cloud-platforms
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Docker | in_db |
Deployment and Runtime Configuration
deployment-and-runtime-configuration
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Kubernetes | in_db |
Container Orchestration Platforms
container-orchestration-platforms
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Kubernetes | in_db |
Kubernetes for ML Workloads
kubernetes-for-ml-workloads
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved | |
| SQL | in_db |
Pega Programming Languages & DSLs
pega-programming-languages-dsls
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| SQL | in_db |
Programming Languages for Data Work
programming-languages-for-data-work
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| NoSQL | in_db |
NoSQL Databases
nosql-databases
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| API Integration | in_db |
API Integration and Data Fetching
api-integration-and-data-fetching
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| API Integration | in_db |
Cross-Platform App Languages
cross-platform-app-languages
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| API Integration | in_db |
Networking and API Integration
networking-and-api-integration
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Library artifacts (this run)
| Kind | Detail | DB id |
|---|---|---|
| canonical_skill_proposed | Tesseract | type=Optical Character Recognition subtype=general nature=TOOL lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Google Vision API | type=Cloud Services subtype=general nature=PLATFORM lifespan=MULTI_YEAR | |
| canonical_skill_proposed | AWS Textract | type=Cloud Services subtype=general nature=PLATFORM lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Natural Language Processing | type=Concepts subtype=general nature=CONCEPT lifespan=EVERGREEN | |
| canonical_skill_proposed | OpenCV | type=Computer Vision Libraries subtype=general nature=TOOL lifespan=MULTI_YEAR | |
| canonical_skill_proposed | PIL | type=Image Processing Libraries subtype=general nature=TOOL lifespan=MULTI_YEAR | |
| canonical_skill_proposed | SpaCy | type=Natural Language Processing Libraries subtype=general nature=TOOL lifespan=MULTI_YEAR | |
| canonical_skill_proposed | NLTK | type=Natural Language Processing Libraries subtype=general nature=TOOL lifespan=MULTI_YEAR | |
| canonical_skill_proposed | API Development | type=Development Practices subtype=general nature=PRACTICE lifespan=MULTI_YEAR | |
| dimension_skill_link_proposed | Google Cloud ↔ Cloud & Hosting Providers | |
| dimension_skill_link_proposed | Google Cloud ↔ Cloud Provider Platforms | |
| dimension_skill_link_proposed | Google Cloud ↔ Cloud Security Posture Tools |
nano JD Parser — gpt-4.1-nano click to toggle
Show raw JSON
{
"JD_type": "pass",
"about_company": null,
"certifications": [],
"company_name": "Microvista Technologies",
"ctc": null,
"domain": {
"primary": {
"aliases": [
"ITES",
"BPO",
"Tech Consulting"
],
"domain": "IT Services \u0026 Consulting"
},
"secondary": null
},
"education": [
{
"level": "Bachelor\u0027s",
"qualification": "BTECH/BE/MTECH/ME - Computer Science / Engineering (or related)",
"raw": "Bachelors or Masters degree in Computer Science, Engineering, or related fields.",
"requirement": "required"
}
],
"experience": {
"max": null,
"min": 3,
"raw": "3+ years of professional experience in Python development."
},
"job_locations": [],
"role": "Python Developer",
"role_aliases": [
"Python Engineer",
"Software Developer",
"SWE"
],
"role_archetype": "Engineering",
"roles_and_responsibilities": [
{
"bullet_count": 0,
"heading": "Position Overview",
"heading_was_present": true,
"source_marker": {
"first_5_words": "We are seeking a highly",
"last_5_words": "technical and business requirements."
},
"text": "We are seeking a highly skilled Python Developer with over 3 years of experience, specializing in Optical Character Recognition (OCR) and Artificial Intelligence/Machine Learning (AI/ML) technologies. The ideal candidate will be responsible for designing, implementing, and optimizing AI-driven solutions and OCR systems to meet the organization\u0027s technical and business requirements.",
"word_count": 52
},
{
"bullet_count": 0,
"heading": "Key Responsibilities",
"heading_was_present": true,
"source_marker": {
"first_5_words": "Python Development: Develop, test,",
"last_5_words": "and troubleshooting for deployed systems."
},
"text": "Python Development:\nDevelop, test, and maintain scalable Python applications and scripts.\nOptimize existing codebases for performance, readability, and maintainability.\n\nOCR Implementation\nDesign and integrate OCR solutions using tools like Tesseract, Google Vision API, or AWS Textract.\nEnhance OCR models with preprocessing techniques such as noise removal, binarization, and image enhancement.\nHandle extraction, parsing, and validation of structured and unstructured data from scanned documents.\n\nAI/ML Development\nDevelop and train machine learning models using frameworks like TensorFlow, PyTorch, or Scikit-learn.\nImplement Natural Language Processing (NLP) for document classification and data extraction.\nContinuously fine-tune AI models to improve accuracy and efficiency.\n\nIntegration And Deployment\nDeploy AI/ML solutions into production environments.\nEnsure seamless integration with existing systems and applications.\n\nData Management\nWork with large datasets, including data preprocessing, augmentation, and analysis.\nCollaborate with data engineers to design pipelines for continuous data processing.\n\nCollaboration\nWork closely with cross-functional teams, including product managers, UI/UX designers, and data scientists.\nTranslate business requirements into technical specifications and solutions.\n\nDocumentation And Support\nDocument code, processes, and best practices.\nProvide technical support and troubleshooting for deployed systems.",
"word_count": 335
},
{
"bullet_count": 0,
"heading": "Qualifications And Skills",
"heading_was_present": true,
"source_marker": {
"first_5_words": "Educational Background: Bachelors or",
"last_5_words": "development and integration."
},
"text": "Educational Background: Bachelors or Masters degree in Computer Science, Engineering, or related fields.\n\nExperience\n3+ years of professional experience in Python development.\nProven experience with OCR tools and frameworks (e.g., Tesseract, OpenCV, ABBYY, Keras-OCR).\nStrong understanding of AI/ML concepts, algorithms, and frameworks.\n\nTechnical Skills\nHands-on experience with machine learning frameworks (TensorFlow, PyTorch, or Scikit-learn).\nProficiency in image processing libraries (e.g., OpenCV, PIL).\nExperience in NLP libraries like SpaCy or NLTK is a plus.\nKnowledge of cloud-based AI/ML services (AWS, Google Cloud, Azure).\n\nSoft Skills\nStrong problem-solving and analytical skills.\nExcellent verbal and written communication abilities.\nAbility to work both independently and collaboratively in a team environment.\n\nPreferred Skills\nKnowledge of DevOps practices and containerization (Docker, Kubernetes).\nFamiliarity with databases (SQL and NoSQL).\nExperience in API development and integration.",
"word_count": 265
}
],
"urls": [
{
"type": "website",
"url": "https://www.microvistatech.com/"
}
]
}
API 1 — extract-from-jd click to toggle
{
"final_skills": [
{
"is_primary": true,
"skill_name": "Python"
},
{
"is_primary": true,
"skill_name": "OCR"
},
{
"is_primary": true,
"skill_name": "Artificial Intelligence"
},
{
"is_primary": true,
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{
"is_primary": true,
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},
{
"is_primary": true,
"skill_name": "Google Vision API"
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{
"is_primary": true,
"skill_name": "AWS Textract"
},
{
"is_primary": true,
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{
"is_primary": true,
"skill_name": "PyTorch"
},
{
"is_primary": true,
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{
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{
"is_primary": true,
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{
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},
{
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},
{
"is_primary": false,
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},
{
"is_primary": false,
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},
{
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{
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{
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{
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},
{
"is_primary": false,
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},
{
"is_primary": false,
"skill_name": "NoSQL"
},
{
"is_primary": false,
"skill_name": "API Development"
},
{
"is_primary": false,
"skill_name": "API Integration"
}
],
"jd_role": {
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"Python Engineer",
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"slug": ""
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"nano_parsed": {
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"heading": "Position Overview",
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"source_marker": {
"first_5_words": "We are seeking a highly",
"last_5_words": "technical and business requirements."
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"text": "We are seeking a highly skilled Python Developer with over 3 years of experience, specializing in Optical Character Recognition (OCR) and Artificial Intelligence/Machine Learning (AI/ML) technologies. The ideal candidate will be responsible for designing, implementing, and optimizing AI-driven solutions and OCR systems to meet the organization\u0027s technical and business requirements.",
"word_count": 52
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{
"bullet_count": 0,
"heading": "Key Responsibilities",
"heading_was_present": true,
"source_marker": {
"first_5_words": "Python Development: Develop, test,",
"last_5_words": "and troubleshooting for deployed systems."
},
"text": "Python Development:\nDevelop, test, and maintain scalable Python applications and scripts.\nOptimize existing codebases for performance, readability, and maintainability.\n\nOCR Implementation\nDesign and integrate OCR solutions using tools like Tesseract, Google Vision API, or AWS Textract.\nEnhance OCR models with preprocessing techniques such as noise removal, binarization, and image enhancement.\nHandle extraction, parsing, and validation of structured and unstructured data from scanned documents.\n\nAI/ML Development\nDevelop and train machine learning models using frameworks like TensorFlow, PyTorch, or Scikit-learn.\nImplement Natural Language Processing (NLP) for document classification and data extraction.\nContinuously fine-tune AI models to improve accuracy and efficiency.\n\nIntegration And Deployment\nDeploy AI/ML solutions into production environments.\nEnsure seamless integration with existing systems and applications.\n\nData Management\nWork with large datasets, including data preprocessing, augmentation, and analysis.\nCollaborate with data engineers to design pipelines for continuous data processing.\n\nCollaboration\nWork closely with cross-functional teams, including product managers, UI/UX designers, and data scientists.\nTranslate business requirements into technical specifications and solutions.\n\nDocumentation And Support\nDocument code, processes, and best practices.\nProvide technical support and troubleshooting for deployed systems.",
"word_count": 335
},
{
"bullet_count": 0,
"heading": "Qualifications And Skills",
"heading_was_present": true,
"source_marker": {
"first_5_words": "Educational Background: Bachelors or",
"last_5_words": "development and integration."
},
"text": "Educational Background: Bachelors or Masters degree in Computer Science, Engineering, or related fields.\n\nExperience\n3+ years of professional experience in Python development.\nProven experience with OCR tools and frameworks (e.g., Tesseract, OpenCV, ABBYY, Keras-OCR).\nStrong understanding of AI/ML concepts, algorithms, and frameworks.\n\nTechnical Skills\nHands-on experience with machine learning frameworks (TensorFlow, PyTorch, or Scikit-learn).\nProficiency in image processing libraries (e.g., OpenCV, PIL).\nExperience in NLP libraries like SpaCy or NLTK is a plus.\nKnowledge of cloud-based AI/ML services (AWS, Google Cloud, Azure).\n\nSoft Skills\nStrong problem-solving and analytical skills.\nExcellent verbal and written communication abilities.\nAbility to work both independently and collaboratively in a team environment.\n\nPreferred Skills\nKnowledge of DevOps practices and containerization (Docker, Kubernetes).\nFamiliarity with databases (SQL and NoSQL).\nExperience in API development and integration.",
"word_count": 265
}
],
"urls": [
{
"type": "website",
"url": "https://www.microvistatech.com/"
}
]
},
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"rejection_reason": null,
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]
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"PIL",
"SpaCy",
"NLTK",
"AWS",
"Google Cloud",
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"queued": false,
"reasoning": "Domain=AI / ML; The JD centers on building and training Python-based OCR and AI/ML solutions, which aligns best with ML Engineer rather than a pure CV or MLOps role.",
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},
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"centroid_updated": true,
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},
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}
API 2 — extract-details
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},
{
"alias_persist_skipped_reason": "TODO: REMOVE AFTER TESTING \u2014 alias DB write disabled",
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"new_alias_text": null,
"new_skill_meta": null,
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},
{
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{
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"id": 271,
"is_primary": true,
"match_strategy": "CASE_INSENSITIVE"
}
],
"canonical": {
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"display_name": "SQL",
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"is_also_category": false,
"is_extractable": true,
"skill_nature": "LANGUAGE",
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"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"dimensions": [
{
"dimension": {
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"display_name": "Pega Programming Languages \u0026 DSLs",
"id": 267,
"rationale": "Programming languages and domain-specific languages used in Pega development.",
"slug": "pega-programming-languages-dsls",
"source": "db"
},
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"llm_role": null,
"roles_from_db": [
{
"display_name": "Pega Developer",
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}
]
},
{
"dimension": {
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"display_name": "Programming Languages for Data Work",
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"rationale": "Languages used to implement data pipelines, transformations, and operational glue. This is the primary coding surface for building ingestion, enrichment, and automation logic in data engineering.",
"slug": "programming-languages-for-data-work",
"source": "db"
},
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"roles_from_db": [
{
"display_name": "Data Engineer",
"id": 2,
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}
]
}
],
"input_skill": "SQL",
"matched_via": "alias",
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": null,
"source_tag": "db",
"was_in_llm_skills": true
},
{
"aliases_in_db": [
{
"alias_text": "NoSQL",
"alias_type": "CANONICAL",
"id": 1989,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
}
],
"canonical": {
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"display_name": "NoSQL",
"id": 1346,
"is_also_category": false,
"is_extractable": true,
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},
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{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "NoSQL Databases",
"id": 19,
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"slug": "nosql-databases",
"source": "db"
},
"input_skill": "NoSQL",
"llm_role": null,
"roles_from_db": [
{
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}
]
}
],
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"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": null,
"source_tag": "db",
"was_in_llm_skills": true
},
{
"aliases_in_db": [],
"canonical": null,
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"input_skill": "API Development",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "Development Practices",
"skill_nature": "PRACTICE",
"sub_category": "general",
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},
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"merge_log": [],
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"relationships": null,
"skill_id": "api-development",
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"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [
{
"alias_text": "API Integration",
"alias_type": "CANONICAL",
"id": 2559,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
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],
"canonical": {
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"is_extractable": true,
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"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"dimensions": [
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "API Integration and Data Fetching",
"id": 127,
"rationale": "Client-side integration with backend endpoints and third-party services, including request shaping, response handling, and synchronization with UI state. This is central to frontend work because most screens depend on remote data.",
"slug": "api-integration-and-data-fetching",
"source": "db"
},
"input_skill": "API Integration",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Angular Frontend Developer",
"id": 90,
"rationale": null,
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"slug": "angular-frontend-developer",
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},
{
"display_name": "Frontend Developer",
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"role_archetype": null,
"slug": "frontend-engineer",
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},
{
"display_name": "Fullstack Developer",
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"rationale": null,
"role_archetype": null,
"slug": "full-stack-engineer",
"source": "db"
},
{
"display_name": "React Frontend Developer",
"id": 89,
"rationale": null,
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"slug": "react-frontend-developer",
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},
{
"display_name": "Svelte Frontend Developer",
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"rationale": null,
"role_archetype": "Engineering",
"slug": "svelte-frontend-developer",
"source": "db"
},
{
"display_name": "Vue Frontend Developer",
"id": 91,
"rationale": null,
"role_archetype": "Engineering",
"slug": "vue-frontend-developer",
"source": "db"
},
{
"display_name": "Web Developer",
"id": 25,
"rationale": null,
"role_archetype": null,
"slug": "web-developer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Cross-Platform App Languages",
"id": 167,
"rationale": "Languages used to implement shared mobile features across iOS and Android from a common codebase. This is the primary coding surface for hybrid app logic, UI behavior, and platform-specific branching.",
"slug": "cross-platform-app-languages",
"source": "db"
},
"input_skill": "API Integration",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Hybrid Mobile Developer",
"id": 11,
"rationale": null,
"role_archetype": null,
"slug": "hybrid-mobile-developer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Networking and API Integration",
"id": 84,
"rationale": "Client-side HTTP communication with backend services, including request construction, response parsing, retries, and error handling. iOS engineers use this to connect native screens to server-owned APIs.",
"slug": "networking-and-api-integration",
"source": "db"
},
"input_skill": "API Integration",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Android Developer",
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"rationale": null,
"role_archetype": null,
"slug": "android-engineer",
"source": "db"
},
{
"display_name": "Hybrid Mobile Developer",
"id": 11,
"rationale": null,
"role_archetype": null,
"slug": "hybrid-mobile-developer",
"source": "db"
},
{
"display_name": "Native Mobile Developer",
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"rationale": null,
"role_archetype": "Engineering",
"slug": "native-mobile-developer",
"source": "db"
},
{
"display_name": "iOS Developer",
"id": 6,
"rationale": null,
"role_archetype": null,
"slug": "ios-engineer",
"source": "db"
}
]
}
],
"input_skill": "API Integration",
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"new_alias_text": null,
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"was_in_llm_skills": true
}
],
"unmatched_skills": [
"Tesseract",
"Google Vision API",
"AWS Textract",
"Natural Language Processing",
"OpenCV",
"PIL",
"SpaCy",
"NLTK",
"API Development"
]
}
API 3 — final-role-output
{
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"role_archetype": null,
"slug": "ml-engineer",
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},
"chosen_role_resolution": "in_db",
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{
"skill": "Python",
"tag": "in_db"
},
{
"skill": "OCR",
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},
{
"skill": "Artificial Intelligence",
"tag": "in_db"
},
{
"skill": "Machine Learning",
"tag": "in_db"
},
{
"skill": "Tesseract",
"tag": "new"
},
{
"skill": "Google Vision API",
"tag": "new"
},
{
"skill": "AWS Textract",
"tag": "new"
},
{
"skill": "TensorFlow",
"tag": "in_db"
},
{
"skill": "PyTorch",
"tag": "in_db"
},
{
"skill": "Scikit-learn",
"tag": "in_db"
},
{
"skill": "Natural Language Processing",
"tag": "new"
},
{
"skill": "OpenCV",
"tag": "new"
},
{
"skill": "PIL",
"tag": "new"
},
{
"skill": "SpaCy",
"tag": "new"
},
{
"skill": "NLTK",
"tag": "new"
},
{
"skill": "AWS",
"tag": "in_db"
},
{
"skill": "Google Cloud",
"tag": "in_db"
},
{
"skill": "Azure",
"tag": "in_db"
},
{
"skill": "DevOps",
"tag": "in_db"
},
{
"skill": "Docker",
"tag": "in_db"
},
{
"skill": "Kubernetes",
"tag": "in_db"
},
{
"skill": "SQL",
"tag": "in_db"
},
{
"skill": "NoSQL",
"tag": "in_db"
},
{
"skill": "API Development",
"tag": "new"
},
{
"skill": "API Integration",
"tag": "in_db"
}
],
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"llm_cost_api2_usd": null,
"llm_cost_api3_usd": null,
"llm_cost_total_usd": null,
"persistence": {
"items": [
{
"chosen_role_id": 3,
"dimension": {
"difficulty_hint": "well_known",
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"id": 248,
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"source": "db"
},
"dimension_id": 248,
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"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Cloud Security Engineer",
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"role_archetype": null,
"slug": "cloud-security-engineer",
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}
],
"skill_dimension_saved": true,
"skill_id": 5,
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"skipped_reason": null
},
{
"chosen_role_id": 3,
"dimension": {
"difficulty_hint": "well_known",
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},
"dimension_id": 1,
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"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Backend Developer",
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},
{
"display_name": "Fullstack Developer",
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}
],
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"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 3,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages and Scripting",
"id": 59,
"rationale": "Languages used to write security automation, analysis scripts, detection logic, and remediation helpers. This is the primary implementation surface for a cybersecurity engineer across tooling and response workflows.",
"slug": "programming-languages-and-scripting",
"source": "db"
},
"dimension_id": 59,
"input_skill": "Python",
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"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Cyber Security Engineer",
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"rationale": null,
"role_archetype": null,
"slug": "cybersecurity-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
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"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 3,
"dimension": {
"difficulty_hint": "well_known",
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"rationale": "Languages used to implement data pipelines, transformations, and operational glue. This is the primary coding surface for building ingestion, enrichment, and automation logic in data engineering.",
"slug": "programming-languages-for-data-work",
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},
"dimension_id": 21,
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"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Data Engineer",
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}
],
"skill_dimension_saved": true,
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"skipped_reason": null
},
{
"chosen_role_id": 3,
"dimension": {
"difficulty_hint": "well_known",
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"rationale": "Languages used to build training code, inference services, evaluation jobs, and ML glue code. This is the primary implementation surface for ML engineers across experimentation and productionization.",
"slug": "programming-languages-for-ml-systems",
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},
"dimension_id": 39,
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"matched_chosen_role": true,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
"role_dimension_saved": true,
"roles_from_db": [
{
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"slug": "ml-engineer",
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},
{
"display_name": "MLOps Engineer",
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}
],
"skill_dimension_saved": true,
"skill_id": 5,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 3,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages for XR",
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"rationale": "Primary implementation languages used to build immersive client features, interaction logic, and device-specific runtime behavior. This is the core coding surface for AR/VR experiences.",
"slug": "programming-languages-for-xr",
"source": "db"
},
"dimension_id": 97,
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"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "AR/VR Engineer",
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"role_archetype": null,
"slug": "ar-vr-engineer",
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}
],
"skill_dimension_saved": true,
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"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 3,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Python Programming",
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"rationale": "Core Python language skills used to implement backend business logic, request handlers, integrations, and service internals. This is the primary coding surface for the role.",
"slug": "python-programming",
"source": "db"
},
"dimension_id": 290,
"input_skill": "Python",
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"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Python Backend Developer",
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"rationale": null,
"role_archetype": "Engineering",
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}
],
"skill_dimension_saved": true,
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"skill_tag": "in_db",
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},
{
"chosen_role_id": 3,
"dimension": {
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"display_name": "React Frontend Development",
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"rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
"slug": "d_init_01",
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},
"dimension_id": 96,
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"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
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"skill_id": 1577,
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},
{
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"display_name": "React Frontend Development",
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},
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},
{
"chosen_role_id": 3,
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"display_name": "AI Governance and Model Security",
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"rationale": "Controls and documentation used to make models safer, auditable, and compliant. ML engineers use this to manage model risk, supply chain integrity, and governance requirements.",
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},
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"role_dimension_saved": true,
"roles_from_db": [
{
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},
{
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},
{
"display_name": "MLOps Engineer",
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"role_archetype": null,
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}
],
"skill_dimension_saved": true,
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},
{
"chosen_role_id": 3,
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"display_name": "React Frontend Development",
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"rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
"slug": "d_init_01",
"source": "db"
},
"dimension_id": 96,
"input_skill": "Machine Learning",
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"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
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"skill_dimension_saved": true,
"skill_id": 1356,
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},
{
"chosen_role_id": 3,
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},
"dimension_id": 40,
"input_skill": "TensorFlow",
"llm_role": null,
"matched_chosen_role": true,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
"role_dimension_saved": true,
"roles_from_db": [
{
"display_name": "ML Engineer",
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"slug": "ml-engineer",
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LLM Calls
Every model call made for this run, in pipeline order. Click a card to see the model's response.