Pipeline run
be435ee7-8877-402f-b968-6e7488a6e021
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 focuses on developing, validating, documenting, and integrating machine learning models and AI components, which best matches an ML Engineer.
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, TensorFlow, PyTorch, Natural Language Processing, Machine Learning Algorithms, Large Language Models (LLM), RAG, Job Overview We are seeking a Junior AI Analyst to join our dynamic team at Huemn's Hyderabad office on a full-time basis. The ideal candidate will have 1 to 3 years of experience and a strong background in developing and applying machine learning models. This role requires a combination of technical proficiency and an understanding of photography industry needs to help us continue to innovate our products and services. Qualifications And Skills • Proficiency in Python is critical for developing and implementing machine learning models (Mandatory skill). • Strong understanding of various machine learning algorithms, necessary for enhancing our AI capabilities (Mandatory skill). • Familiarity with Large Language Models (LLM) for natural language processing applications (Mandatory skill). • Experience with TensorFlow to build and train machine learning models that solve complex tasks. • Knowledge of PyTorch for deep learning projects that require flexibility and computational efficiency. • Skilled in Natural Language Processing tools and techniques to improve user interaction with our platform. • Understanding of RAG techniques to help refine recommendation systems for client galleries. • Ability to work collaboratively across teams, understanding team management tools essential for project success. Roles And Responsibilities • Develop and maintain machine learning models that enhance the intelligence and efficiency of our studio management tool. • Collaborate with cross-functional teams to integrate AI solutions that meet photography industry standards. • Analyze data trends to inform future AI projects and drive innovation within the team. • Participate in code reviews, sharing knowledge and best practices to improve software quality. • Conduct experiments to validate the effectiveness of AI models and iterate based on feedback and results. • Prepare comprehensive documentation to support the understanding and maintenance of AI algorithms. • Work closely with frontend and backend developers to ensure seamless integration of AI components. • Stay updated with the latest developments in AI and machine learning to continually enhance our offerings.
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
- 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) |
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
- Code Review (CANONICAL)
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- SoftSkill
- Sub-category
- Code Review
- Confidence
- 0.96
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Code review is a standard hiring-pipeline requirement in engineering JDs and is built into major platforms like GitHub/GitLab pull-request workflows, indicating broad adoption.
Skill profile (library / DB)
- Skill nature
- PRACTICE
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 58
- Sub-category id
- 364
- 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) |
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Soft Skills
- Sub-category
- general
- Skill nature
- PRACTICE
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Version strategy
- UNVERSIONED
Aliases — catalog
- Frontend (CANONICAL)
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Domain
- Sub-category
- Frontend Development
- Confidence
- 0.93
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Frontend is a hiring-pipeline staple: job postings routinely require HTML/CSS/JavaScript plus React/Angular/Vue, and major platforms (e.g., Stack Overflow survey, GitHub repos) show sustained high usage.
Skill profile (library / DB)
- Skill nature
- CONCEPT
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 37
- Sub-category id
- 1256
- 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) |
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Software Development
- Sub-category
- general
- Skill nature
- CONCEPT
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
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 |
|---|---|---|---|---|---|---|
| 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) | |
| Artificial Intelligence | in_db |
React Frontend Development
d_init_01
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Code Review | in_db |
React Frontend Development
d_init_01
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Frontend | in_db |
React Frontend Development
d_init_01
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Library artifacts (this run)
| Kind | Detail | DB id |
|---|---|---|
| canonical_skill_proposed | Documentation | type=Soft Skills subtype=general nature=PRACTICE lifespan=EVERGREEN | |
| canonical_skill_proposed | Backend | type=Software Development subtype=general nature=CONCEPT lifespan=MULTI_YEAR |
nano JD Parser — gpt-4.1-nano click to toggle
Show raw JSON
{
"JD_type": "pass",
"about_company": null,
"certifications": [],
"company_name": "Huemn",
"ctc": null,
"domain": {
"primary": {
"aliases": [],
"domain": "Other"
},
"secondary": null
},
"education": [],
"experience": {
"max": 3,
"min": 1,
"raw": "1 to 3 years of experience"
},
"job_locations": [
{
"aliases": [
"Hyderabad, AP"
],
"city": "Hyderabad",
"country": "India",
"state": null,
"work_mode": "onsite"
}
],
"role": "Junior AI Analyst",
"role_aliases": [
"AI Analyst",
"Machine Learning Analyst",
"Data Analyst"
],
"role_archetype": "Data",
"roles_and_responsibilities": [
{
"bullet_count": 8,
"heading": "Roles And Responsibilities",
"heading_was_present": true,
"source_marker": {
"first_5_words": "\u2022 Develop and maintain machine",
"last_5_words": "enhance our offerings."
},
"text": "\u2022 Develop and maintain machine learning models that enhance the intelligence and efficiency of our studio management tool.\n\u2022 Collaborate with cross-functional teams to integrate AI solutions that meet photography industry standards.\n\u2022 Analyze data trends to inform future AI projects and drive innovation within the team.\n\u2022 Participate in code reviews, sharing knowledge and best practices to improve software quality.\n\u2022 Conduct experiments to validate the effectiveness of AI models and iterate based on feedback and results.\n\u2022 Prepare comprehensive documentation to support the understanding and maintenance of AI algorithms.\n\u2022 Work closely with frontend and backend developers to ensure seamless integration of AI components.\n\u2022 Stay updated with the latest developments in AI and machine learning to continually enhance our offerings.",
"word_count": 108
}
],
"urls": []
}
API 1 — extract-from-jd click to toggle
{
"final_skills": [
{
"is_primary": true,
"skill_name": "Machine Learning"
},
{
"is_primary": true,
"skill_name": "Artificial Intelligence"
},
{
"is_primary": false,
"skill_name": "Code Review"
},
{
"is_primary": false,
"skill_name": "Documentation"
},
{
"is_primary": false,
"skill_name": "Frontend"
},
{
"is_primary": false,
"skill_name": "Backend"
}
],
"jd_role": {
"display_name": "Junior AI Analyst",
"rationale": null,
"role_aliases": [
"AI Analyst",
"Machine Learning Analyst",
"Data Analyst"
],
"role_archetype": "Data",
"slug": ""
},
"nano_parsed": {
"JD_type": "pass",
"about_company": null,
"certifications": [],
"company_name": "Huemn",
"ctc": null,
"domain": {
"primary": {
"aliases": [],
"domain": "Other"
},
"secondary": null
},
"education": [],
"experience": {
"max": 3,
"min": 1,
"raw": "1 to 3 years of experience"
},
"job_locations": [
{
"aliases": [
"Hyderabad, AP"
],
"city": "Hyderabad",
"country": "India",
"state": null,
"work_mode": "onsite"
}
],
"role": "Junior AI Analyst",
"role_aliases": [
"AI Analyst",
"Machine Learning Analyst",
"Data Analyst"
],
"role_archetype": "Data",
"roles_and_responsibilities": [
{
"bullet_count": 8,
"heading": "Roles And Responsibilities",
"heading_was_present": true,
"source_marker": {
"first_5_words": "\u2022 Develop and maintain machine",
"last_5_words": "enhance our offerings."
},
"text": "\u2022 Develop and maintain machine learning models that enhance the intelligence and efficiency of our studio management tool.\n\u2022 Collaborate with cross-functional teams to integrate AI solutions that meet photography industry standards.\n\u2022 Analyze data trends to inform future AI projects and drive innovation within the team.\n\u2022 Participate in code reviews, sharing knowledge and best practices to improve software quality.\n\u2022 Conduct experiments to validate the effectiveness of AI models and iterate based on feedback and results.\n\u2022 Prepare comprehensive documentation to support the understanding and maintenance of AI algorithms.\n\u2022 Work closely with frontend and backend developers to ensure seamless integration of AI components.\n\u2022 Stay updated with the latest developments in AI and machine learning to continually enhance our offerings.",
"word_count": 108
}
],
"urls": []
},
"rejected": false,
"rejection_reason": null,
"run_id": "be435ee7-8877-402f-b968-6e7488a6e021",
"stage3_signals": {
"alias_found": true,
"alias_match_roles": [
{
"display_name": "Data Analyst",
"kra_matches": null,
"matched_count": null,
"matched_skills": null,
"role_id": 143,
"score": 1.0,
"slug": "data-analyst",
"total_count": null
}
],
"kra_match_roles": [
{
"display_name": "AI Engineer",
"kra_matches": [
{
"kra_text": "Defines evaluation frameworks, automated test suites, and human feedback loops to measure AI feature quality, accuracy, and consistency.",
"sentence": "Conduct experiments to validate the effectiveness of AI models and iterate based on feedback and results.",
"similarity": 0.6201
},
{
"kra_text": "Integrates AI model API responses with application business logic, database writes, event publishing, and downstream service orchestration.",
"sentence": "Work closely with frontend and backend developers to ensure seamless integration of AI components.",
"similarity": 0.5788
},
{
"kra_text": "Defines evaluation frameworks, automated test suites, and human feedback loops to measure AI feature quality, accuracy, and consistency.",
"sentence": "Prepare comprehensive documentation to support the understanding and maintenance of AI algorithms.",
"similarity": 0.5283
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 13,
"score": 0.5757,
"slug": "ai-engineer",
"total_count": null
},
{
"display_name": "AI Compliance Officer",
"kra_matches": [
{
"kra_text": "Maintains audit trail documentation, evidence records, and compliance certification artifacts for AI system approvals and regulatory review.",
"sentence": "Prepare comprehensive documentation to support the understanding and maintenance of AI algorithms.",
"similarity": 0.5948
},
{
"kra_text": "Evaluates AI models for bias in protected attributes, explainability limitations, and transparency requirements in automated decision-making contexts.",
"sentence": "Conduct experiments to validate the effectiveness of AI models and iterate based on feedback and results.",
"similarity": 0.5178
},
{
"kra_text": "Monitors deployed AI systems for compliance policy drift, regulatory changes, and emerging requirements affecting existing AI deployments.",
"sentence": "Analyze data trends to inform future AI projects and drive innovation within the team.",
"similarity": 0.517
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 12,
"score": 0.5432,
"slug": "ai-compliance-officer",
"total_count": null
},
{
"display_name": "Flutter Developer",
"kra_matches": [
{
"kra_text": "collaborate with design, product, and backend teams",
"sentence": "Work closely with frontend and backend developers to ensure seamless integration of AI components.",
"similarity": 0.5756
},
{
"kra_text": "collaborate with design, product, and backend teams",
"sentence": "Collaborate with cross-functional teams to integrate AI solutions that meet photography industry standards.",
"similarity": 0.5097
},
{
"kra_text": "collaborate with design, product, and backend teams",
"sentence": "Participate in code reviews, sharing knowledge and best practices to improve software quality.",
"similarity": 0.4451
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 74,
"score": 0.5102,
"slug": "flutter-developer",
"total_count": null
},
{
"display_name": "React Native Developer",
"kra_matches": [
{
"kra_text": "maintain code quality",
"sentence": "Participate in code reviews, sharing knowledge and best practices to improve software quality.",
"similarity": 0.6237
},
{
"kra_text": "integrate backend APIs",
"sentence": "Work closely with frontend and backend developers to ensure seamless integration of AI components.",
"similarity": 0.5478
},
{
"kra_text": "integrate backend APIs",
"sentence": "Collaborate with cross-functional teams to integrate AI solutions that meet photography industry standards.",
"similarity": 0.3538
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 73,
"score": 0.5085,
"slug": "react-native-developer",
"total_count": null
},
{
"display_name": "ML Engineer",
"kra_matches": [
{
"kra_text": "Supports offline experimentation, hyperparameter tuning, and online A/B experiments to improve model quality and investigate production performance issues.",
"sentence": "Conduct experiments to validate the effectiveness of AI models and iterate based on feedback and results.",
"similarity": 0.5214
},
{
"kra_text": "Builds model serving infrastructure to deploy trained models as real-time prediction APIs or batch inference jobs using TorchServe, TensorFlow Serving, or SageMaker.",
"sentence": "Develop and maintain machine learning models that enhance the intelligence and efficiency of our studio management tool.",
"similarity": 0.5148
},
{
"kra_text": "Designs end-to-end ML training pipelines and model inference workflows using TensorFlow, PyTorch, or scikit-learn on cloud ML platforms.",
"sentence": "Analyze data trends to inform future AI projects and drive innovation within the team.",
"similarity": 0.4302
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 3,
"score": 0.4888,
"slug": "ml-engineer",
"total_count": null
}
],
"skill_match_roles": [
{
"display_name": "ML Engineer",
"kra_matches": null,
"matched_count": 1,
"matched_skills": [
"Machine Learning"
],
"role_id": 3,
"score": 0.5,
"slug": "ml-engineer",
"total_count": 2
},
{
"display_name": "AI Engineer",
"kra_matches": null,
"matched_count": 1,
"matched_skills": [
"Machine Learning"
],
"role_id": 13,
"score": 0.5,
"slug": "ai-engineer",
"total_count": 2
},
{
"display_name": "MLOps Engineer",
"kra_matches": null,
"matched_count": 1,
"matched_skills": [
"Machine Learning"
],
"role_id": 16,
"score": 0.5,
"slug": "ml-ops-engineer",
"total_count": 2
}
]
},
"stage4_decision": {
"alias_collision_detected": false,
"case": "DOMAIN",
"chosen_role": {
"display_name": "ML Engineer",
"kra_matches": null,
"matched_count": null,
"matched_skills": null,
"role_id": 3,
"score": 0.95,
"slug": "ml-engineer",
"total_count": null
},
"confidence": 0.95,
"is_new_role": false,
"llm2_fired": false,
"llm2_reasoning": null,
"matched_dimensions": [
"Machine Learning Model Development",
"AI Solution Integration",
"Model Experimentation and Validation",
"Cross-functional Collaboration",
"Software Quality Improvement",
"Technical Documentation",
"AI Product Enhancement"
],
"matched_kras": [
"Develop and maintain machine learning models",
"Integrate AI solutions that meet photography industry standards",
"Analyze data trends to inform future AI projects",
"Participate in code reviews",
"Conduct experiments to validate the effectiveness of AI models",
"Prepare comprehensive documentation",
"Work closely with frontend and backend developers",
"Stay updated with the latest developments in AI and machine learning"
],
"matched_skills": [
"machine learning models",
"AI solutions",
"data trends",
"code reviews",
"experiments",
"documentation",
"AI algorithms",
"frontend and backend developers"
],
"new_role_display_name": null,
"new_role_slug": null,
"queued": false,
"reasoning": "Domain=AI / ML; The JD focuses on developing, validating, documenting, and integrating machine learning models and AI components, which best matches an ML Engineer.",
"sub_role": null
},
"stage5_updates": {
"centroid_n_after": 33,
"centroid_updated": true,
"collision_log_id": null,
"new_kra_attached": null,
"new_skills_attached": [
{
"is_primary": false,
"queue_id": 23463,
"role_display_name": "ML Engineer",
"role_slug": "ml-engineer",
"skill_name": "Documentation",
"status": "pending"
},
{
"is_primary": false,
"queue_id": 23464,
"role_display_name": "ML Engineer",
"role_slug": "ml-engineer",
"skill_name": "Backend",
"status": "pending"
}
],
"queue_entry_id": null,
"v3_pipeline_triggered": false,
"v3_role_slug": null,
"v3_run_id": null
}
}
API 2 — extract-details
{
"alias_matches": [
{
"alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
"alias_persisted": false,
"existing_alias_id": 2015,
"existing_alias_text": "Machine Learning",
"input_term": "Machine Learning",
"matched_canonical": {
"category_id": 2,
"display_name": "Machine Learning",
"id": 1356,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "CONCEPT",
"slug": "machine-learning",
"sub_category_id": 1024,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"matched_via": "alias"
},
{
"alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
"alias_persisted": false,
"existing_alias_id": 2016,
"existing_alias_text": "Artificial Intelligence",
"input_term": "Artificial Intelligence",
"matched_canonical": {
"category_id": 2,
"display_name": "Artificial Intelligence",
"id": 1357,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "CONCEPT",
"slug": "artificial-intelligence",
"sub_category_id": 1020,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"matched_via": "alias"
},
{
"alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
"alias_persisted": false,
"existing_alias_id": 864,
"existing_alias_text": "Code Review",
"input_term": "Code Review",
"matched_canonical": {
"category_id": 58,
"display_name": "Code Review",
"id": 516,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "PRACTICE",
"slug": "code-review",
"sub_category_id": 364,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"matched_via": "alias"
},
{
"alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
"alias_persisted": false,
"existing_alias_id": 2633,
"existing_alias_text": "Frontend",
"input_term": "Frontend",
"matched_canonical": {
"category_id": 37,
"display_name": "Frontend",
"id": 1663,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "CONCEPT",
"slug": "frontend",
"sub_category_id": 1256,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"matched_via": "alias"
}
],
"candidate_roles": [
{
"display_name": "AI Engineer",
"id": 13,
"rationale": null,
"role_archetype": null,
"slug": "ai-engineer",
"source": "db"
},
{
"display_name": "ML Engineer",
"id": 3,
"rationale": null,
"role_archetype": null,
"slug": "ml-engineer",
"source": "db"
},
{
"display_name": "MLOps Engineer",
"id": 16,
"rationale": null,
"role_archetype": null,
"slug": "ml-ops-engineer",
"source": "db"
}
],
"chosen_role": {
"display_name": "ML Engineer",
"id": 3,
"rationale": "Domain=AI / ML; The JD focuses on developing, validating, documenting, and integrating machine learning models and AI components, which best matches an ML Engineer.",
"role_archetype": null,
"slug": "ml-engineer",
"source": "db"
},
"dimensions": [
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "AI Governance and Model Security",
"id": 50,
"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.",
"slug": "ai-governance-and-model-security",
"source": "db"
},
"input_skill": "Machine Learning",
"llm_role": null,
"roles_from_db": [
{
"display_name": "AI Engineer",
"id": 13,
"rationale": null,
"role_archetype": null,
"slug": "ai-engineer",
"source": "db"
},
{
"display_name": "ML Engineer",
"id": 3,
"rationale": null,
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},
{
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}
]
},
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},
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},
{
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},
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"roles_from_db": []
},
{
"dimension": {
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},
"input_skill": "Code Review",
"llm_role": null,
"roles_from_db": []
},
{
"dimension": {
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"slug": "d_init_01",
"source": "db"
},
"input_skill": "Frontend",
"llm_role": null,
"roles_from_db": []
}
],
"input_final_skills": [
"Machine Learning",
"Artificial Intelligence",
"Code Review",
"Documentation",
"Frontend",
"Backend"
],
"input_llm_skills": [
"Machine Learning",
"Artificial Intelligence",
"Code Review",
"Documentation",
"Frontend",
"Backend"
],
"new_aliases_persisted": 0,
"run_id": "be435ee7-8877-402f-b968-6e7488a6e021",
"skills_detail": [
{
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}
],
"canonical": {
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"is_also_category": false,
"is_extractable": true,
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},
"dimensions": [
{
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]
},
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},
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}
],
"input_skill": "Machine Learning",
"matched_via": "alias",
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"new_alias_text": null,
"new_skill_meta": null,
"source_tag": "db",
"was_in_llm_skills": true
},
{
"aliases_in_db": [
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],
"canonical": {
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"is_extractable": true,
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},
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},
{
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"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "Soft Skills",
"skill_nature": "PRACTICE",
"sub_category": "general",
"typical_lifespan": "EVERGREEN",
"version_strategy": "UNVERSIONED",
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},
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"keep_log": [],
"locked_dimensions": [],
"merge_log": [],
"placed": null,
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},
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},
{
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}
],
"input_skill": "Frontend",
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},
{
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],
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}
API 3 — final-role-output
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{
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},
{
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{
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},
{
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},
{
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"persistence": {
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"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
"role_dimension_saved": true,
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],
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}
],
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},
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