Pipeline run

e582ac21-06d8-47c5-b04c-d6ce0e182874

Pipeline LLM cost (USD)

API 1: $0.0039 API 2: $0.0000 API 3: $0.0000 Total: $0.0039

Client output enrichment

v2 Skill cluster · Nature of work · AI index · Tech stack maturity · Evidence · KRA description

Nature of work · Machine Learning / Deep Learning

Build ML/DL solutions end-to-end: wrangle data, run experiments, create and fine-tune baseline models, test them against acceptance criteria, and document results while working with product/business teams on releases.

"Conduct ML experiments to understand the feasibility and build baseline models to solve the business problem"

Tech stack maturity

Mainstream Modern cache hit

The role centers on widely adopted ML tooling and Python-based workflows such as PyTorch and TensorFlow, which are characteristic of mainstream modern engineering stacks rather than legacy or bleeding-edge-only environments.

AI index (0 = no AI use, 5 = totally AI-dependent · v2.1)

3.20 / 5

✓ Title match

✓ Has AI skill

✓ AI skill (primary)

· AI skill (secondary)

· On AI team

· Builds AI products

vocab breakdown (legacy)

Assistants (×1): —

Frameworks (×2): —

Models / concepts (×3): fine-tuning, computer vision, ML, Machine Learning, Deep Learning

Evidence — skills matched in JD (18)

Machine Learning Deep Learning Analytics Python TensorFlow PyTorch Statistics Mathematics Data Wrangling Preprocessing Post-processing Model Testing Model Building Model Fine-tuning Caffe Azure Computer Vision Natural Language Processing

Skill cluster (5 dimension groups, role-scoped)

ML Frameworks and Libraries

TensorFlow PyTorch

AI Governance and Model Security

Machine Learning

Cloud Platforms

Azure

Programming Languages for ML Systems

Python

Cross-cutting / unaligned

Deep Learning Analytics Statistics Mathematics Data Wrangling Preprocessing Post-processing Model Testing Model Building Model Fine-tuning Caffe Computer Vision Natural Language Processing

Show KRA description ↓

Executes relevant data wrangling activities related to the problem in order to create dataset Conduct ML experiments to understand the feasibility and build baseline models to solve the business problem Fine tune the baseline model for optimum performance Test Models internally per acceptance criteria from business Document relevant Artefacts for communicating with the business Work with product teams in planning and execution of new product releases. Work with cross functional teams - business technology and product teams to understand the product vision; building ML solutions that provides value to the product 4-5 years experience in Deep learning,machine learning & analytics Completed 4 – 5 project sin ML & DL Expertise in machine learning model building lifecycle Clear understanding of various ML techniques with appropriate use to business problems A strong background of statistics and Mathematics Expertise in one of the domains – Computer Vision Language Understanding or structured data Experience in executing collaboratively with engineering design user research teams and business stakeholders Experience with data wrangling techniques preprocessing and post processing requirements for ML solutions Good knowledge python and deep learning frameworks like Tensorflow Pytorch Caffe Familiar with the machine learning model testing approaches Knoledge in Azure deployment Technically strong with the ability to connect the dots Ability to communicate the relevance of technology to the stakeholders in a simple relatable language Curiosity to learn more about new business domains and Technology Innovation An empathetic listener who can give and receive honest thoughtful feedback

Signals

Skill ml-engineer

0.22

Alias ml-engineer

0.60

KRA ml-engineer

0.48

Post-classification

Centroidupdated · n=6

Alias collision log—

New-role queue—

New skills captured13

New KRA captured—

Captured for admin review

Machine Learning primary ↔ ML Engineer pending

Deep Learning primary ↔ ML Engineer pending

Analytics primary ↔ ML Engineer pending

Caffe ↔ ML Engineer pending

Computer Vision ↔ ML Engineer pending

Natural Language Processing ↔ ML Engineer pending

Statistics primary ↔ ML Engineer pending

Mathematics primary ↔ ML Engineer pending

Data Wrangling primary ↔ ML Engineer pending

Preprocessing primary ↔ ML Engineer pending

Model Testing primary ↔ ML Engineer pending

Model Building primary ↔ ML Engineer pending

Model Fine-tuning primary ↔ ML Engineer pending

Status: extract_from_jd_done Created: 2026-05-19T00:30:20.462264Z Updated: 2026-05-19T00:30:21.584451Z

Flow Current 3-step pipeline

1 POST /skills/extract-from-jd

2 POST /skills/extract-details

3 POST /skills/final-role-output

Role Chosen role & resolution

No chosen role stored for this run.

Job description

Senior Associate - Machine Learning Engineer

At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all.

Service Excellence

Role title

Senior Associate – Service Excellence

Location – Bangalore /Trivandrum/Kochi

Job Summary

Global Delivery Services (GDS) is a driving force behind EY’s globalization – currently incorporating Procurement, Talent, Finance and Accounting, IT, Risk management, Talent, Creative Agency, Learning Solutions and Program Execution Services – it aims to achieve effectiveness and efficiency in order to provide sustainable value and is at the core of EY’s most notable transformation projects.

Accountabilities

Executes relevant data wrangling activities related to the problem in order to create dataset
Conduct ML experiments to understand the feasibility and build baseline models to solve the business problem
Fine tune the baseline model for optimum performance
Test Models internally per acceptance criteria from business
Document relevant Artefacts for communicating with the business
Work with product teams in planning and execution of new product releases.
Work with cross functional teams - business technology and product teams to understand the product vision; building ML solutions that provides value to the product


Competencies/ Skills

4-5 years experience in Deep learning,machine learning & analytics
Completed 4 – 5 project sin ML & DL
Expertise in machine learning model building lifecycle
Clear understanding of various ML techniques with appropriate use to business problems
A strong background of statistics and Mathematics
Expertise in one of the domains – Computer Vision Language Understanding or structured data
Experience in executing collaboratively with engineering design user research teams and business stakeholders
Experience with data wrangling techniques preprocessing and post processing requirements for ML solutions
Good knowledge python and deep learning frameworks like Tensorflow Pytorch Caffe
Familiar with the machine learning model testing approaches
Knoledge in Azure deployment


Other Skills

Technically strong with the ability to connect the dots
Ability to communicate the relevance of technology to the stakeholders in a simple relatable language
Curiosity to learn more about new business domains and Technology Innovation
An empathetic listener who can give and receive honest thoughtful feedback


Education

BE/MBA/Pursuing if immediate


EY | Building a better working world 

EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets.

Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform and operate.

Working across assurance, consulting, law, strategy, tax and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today.

Skills from this JD

Each row merges API 1 extraction, API 2 library match / v3 orchestration (dimensions + locked dims), and API 3 persistence tags.

Machine Learning Primary No API 2 row (run stopped after API 1 or history missing)

Deep Learning Primary No API 2 row (run stopped after API 1 or history missing)

Analytics Primary No API 2 row (run stopped after API 1 or history missing)

Python Primary No API 2 row (run stopped after API 1 or history missing)

TensorFlow Primary No API 2 row (run stopped after API 1 or history missing)

PyTorch Primary No API 2 row (run stopped after API 1 or history missing)

Caffe Secondary No API 2 row (run stopped after API 1 or history missing)

Azure Secondary No API 2 row (run stopped after API 1 or history missing)

Computer Vision Secondary No API 2 row (run stopped after API 1 or history missing)

Natural Language Processing Secondary No API 2 row (run stopped after API 1 or history missing)

Statistics Primary No API 2 row (run stopped after API 1 or history missing)

Mathematics Primary No API 2 row (run stopped after API 1 or history missing)

Data Wrangling Primary No API 2 row (run stopped after API 1 or history missing)

Preprocessing Primary No API 2 row (run stopped after API 1 or history missing)

Post-processing Primary No API 2 row (run stopped after API 1 or history missing)

Model Testing Primary No API 2 row (run stopped after API 1 or history missing)

Model Building Primary No API 2 row (run stopped after API 1 or history missing)

Model Fine-tuning Primary No API 2 row (run stopped after API 1 or history missing)

Library artifacts (this run)

No artifact rows for this run.

nano JD Parser — gpt-4.1-nano click to toggle

RoleSenior Associate - Machine Learning Engineer

CompanyEY

Experience4-5 years experience in Deep learning,machine learning & analytics

DomainOther

Location Bangalore, India (null)

JD type pass

Show raw JSON

{
  "JD_type": "pass",
  "about_company": {
    "source_marker": {
      "first_5_words": "EY exists to build a",
      "last_5_words": "facing our world today."
    },
    "text": "EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets.\n\nEnabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform and operate.\n\nWorking across assurance, consulting, law, strategy, tax and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today.",
    "word_count": 64
  },
  "certifications": [],
  "company_name": "EY",
  "ctc": null,
  "domain": {
    "primary": {
      "aliases": [],
      "domain": "Other"
    },
    "secondary": null
  },
  "education": [
    {
      "level": "Bachelor\u0027s",
      "qualification": "BTECH/BE - Any Discipline",
      "raw": "BE/MBA/Pursuing if immediate",
      "requirement": "required"
    }
  ],
  "experience": {
    "max": 5,
    "min": 4,
    "raw": "4-5 years experience in Deep learning,machine learning \u0026 analytics"
  },
  "job_locations": [
    {
      "aliases": [
        "Bengaluru"
      ],
      "city": "Bangalore",
      "country": "India",
      "state": null,
      "work_mode": "null"
    },
    {
      "aliases": [
        "Thiruvananthapuram"
      ],
      "city": "Trivandrum",
      "country": "India",
      "state": null,
      "work_mode": "null"
    },
    {
      "aliases": [],
      "city": "Kochi",
      "country": "India",
      "state": null,
      "work_mode": "null"
    }
  ],
  "role": "Senior Associate - Machine Learning Engineer",
  "role_archetype": "Data",
  "roles_and_responsibilities": [
    {
      "bullet_count": 6,
      "heading": "Accountabilities",
      "heading_was_present": true,
      "source_marker": {
        "first_5_words": "Executes relevant data wrangling",
        "last_5_words": "provides value to the product"
      },
      "text": "Executes relevant data wrangling activities related to the problem in order to create dataset\nConduct ML experiments to understand the feasibility and build baseline models to solve the business problem\nFine tune the baseline model for optimum performance\nTest Models internally per acceptance criteria from business\nDocument relevant Artefacts for communicating with the business\nWork with product teams in planning and execution of new product releases.\nWork with cross functional teams - business technology and product teams to understand the product vision; building ML solutions that provides value to the product",
      "word_count": 66
    },
    {
      "bullet_count": 11,
      "heading": "Competencies/ Skills",
      "heading_was_present": true,
      "source_marker": {
        "first_5_words": "4-5 years experience in Deep",
        "last_5_words": "Knoledge in Azure deployment"
      },
      "text": "4-5 years experience in Deep learning,machine learning \u0026 analytics\nCompleted 4 \u2013 5 project sin ML \u0026 DL\nExpertise in machine learning model building lifecycle\nClear understanding of various ML techniques with appropriate use to business problems\nA strong background of statistics and Mathematics\nExpertise in one of the domains \u2013 Computer Vision Language Understanding or structured data\nExperience in executing collaboratively with engineering design user research teams and business stakeholders\nExperience with data wrangling techniques preprocessing and post processing requirements for ML solutions\nGood knowledge python and deep learning frameworks like Tensorflow Pytorch Caffe\nFamiliar with the machine learning model testing approaches\nKnoledge in Azure deployment",
      "word_count": 113
    },
    {
      "bullet_count": 4,
      "heading": "Other Skills",
      "heading_was_present": true,
      "source_marker": {
        "first_5_words": "Technically strong with the ability",
        "last_5_words": "give and receive honest thoughtful"
      },
      "text": "Technically strong with the ability to connect the dots\nAbility to communicate the relevance of technology to the stakeholders in a simple relatable language\nCuriosity to learn more about new business domains and Technology Innovation\nAn empathetic listener who can give and receive honest thoughtful feedback",
      "word_count": 42
    }
  ],
  "urls": []
}

API 1 — extract-from-jd click to toggle

{
  "final_skills": [
    {
      "is_primary": true,
      "skill_name": "Machine Learning"
    },
    {
      "is_primary": true,
      "skill_name": "Deep Learning"
    },
    {
      "is_primary": true,
      "skill_name": "Analytics"
    },
    {
      "is_primary": true,
      "skill_name": "Python"
    },
    {
      "is_primary": true,
      "skill_name": "TensorFlow"
    },
    {
      "is_primary": true,
      "skill_name": "PyTorch"
    },
    {
      "is_primary": false,
      "skill_name": "Caffe"
    },
    {
      "is_primary": false,
      "skill_name": "Azure"
    },
    {
      "is_primary": false,
      "skill_name": "Computer Vision"
    },
    {
      "is_primary": false,
      "skill_name": "Natural Language Processing"
    },
    {
      "is_primary": true,
      "skill_name": "Statistics"
    },
    {
      "is_primary": true,
      "skill_name": "Mathematics"
    },
    {
      "is_primary": true,
      "skill_name": "Data Wrangling"
    },
    {
      "is_primary": true,
      "skill_name": "Preprocessing"
    },
    {
      "is_primary": true,
      "skill_name": "Post-processing"
    },
    {
      "is_primary": true,
      "skill_name": "Model Testing"
    },
    {
      "is_primary": true,
      "skill_name": "Model Building"
    },
    {
      "is_primary": true,
      "skill_name": "Model Fine-tuning"
    }
  ],
  "jd_role": {
    "display_name": "Senior Associate - Machine Learning Engineer",
    "rationale": null,
    "role_archetype": "Data",
    "slug": ""
  },
  "nano_parsed": {
    "JD_type": "pass",
    "about_company": {
      "source_marker": {
        "first_5_words": "EY exists to build a",
        "last_5_words": "facing our world today."
      },
      "text": "EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets.\n\nEnabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform and operate.\n\nWorking across assurance, consulting, law, strategy, tax and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today.",
      "word_count": 64
    },
    "certifications": [],
    "company_name": "EY",
    "ctc": null,
    "domain": {
      "primary": {
        "aliases": [],
        "domain": "Other"
      },
      "secondary": null
    },
    "education": [
      {
        "level": "Bachelor\u0027s",
        "qualification": "BTECH/BE - Any Discipline",
        "raw": "BE/MBA/Pursuing if immediate",
        "requirement": "required"
      }
    ],
    "experience": {
      "max": 5,
      "min": 4,
      "raw": "4-5 years experience in Deep learning,machine learning \u0026 analytics"
    },
    "job_locations": [
      {
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          "Bengaluru"
        ],
        "city": "Bangalore",
        "country": "India",
        "state": null,
        "work_mode": "null"
      },
      {
        "aliases": [
          "Thiruvananthapuram"
        ],
        "city": "Trivandrum",
        "country": "India",
        "state": null,
        "work_mode": "null"
      },
      {
        "aliases": [],
        "city": "Kochi",
        "country": "India",
        "state": null,
        "work_mode": "null"
      }
    ],
    "role": "Senior Associate - Machine Learning Engineer",
    "role_archetype": "Data",
    "roles_and_responsibilities": [
      {
        "bullet_count": 6,
        "heading": "Accountabilities",
        "heading_was_present": true,
        "source_marker": {
          "first_5_words": "Executes relevant data wrangling",
          "last_5_words": "provides value to the product"
        },
        "text": "Executes relevant data wrangling activities related to the problem in order to create dataset\nConduct ML experiments to understand the feasibility and build baseline models to solve the business problem\nFine tune the baseline model for optimum performance\nTest Models internally per acceptance criteria from business\nDocument relevant Artefacts for communicating with the business\nWork with product teams in planning and execution of new product releases.\nWork with cross functional teams - business technology and product teams to understand the product vision; building ML solutions that provides value to the product",
        "word_count": 66
      },
      {
        "bullet_count": 11,
        "heading": "Competencies/ Skills",
        "heading_was_present": true,
        "source_marker": {
          "first_5_words": "4-5 years experience in Deep",
          "last_5_words": "Knoledge in Azure deployment"
        },
        "text": "4-5 years experience in Deep learning,machine learning \u0026 analytics\nCompleted 4 \u2013 5 project sin ML \u0026 DL\nExpertise in machine learning model building lifecycle\nClear understanding of various ML techniques with appropriate use to business problems\nA strong background of statistics and Mathematics\nExpertise in one of the domains \u2013 Computer Vision Language Understanding or structured data\nExperience in executing collaboratively with engineering design user research teams and business stakeholders\nExperience with data wrangling techniques preprocessing and post processing requirements for ML solutions\nGood knowledge python and deep learning frameworks like Tensorflow Pytorch Caffe\nFamiliar with the machine learning model testing approaches\nKnoledge in Azure deployment",
        "word_count": 113
      },
      {
        "bullet_count": 4,
        "heading": "Other Skills",
        "heading_was_present": true,
        "source_marker": {
          "first_5_words": "Technically strong with the ability",
          "last_5_words": "give and receive honest thoughtful"
        },
        "text": "Technically strong with the ability to connect the dots\nAbility to communicate the relevance of technology to the stakeholders in a simple relatable language\nCuriosity to learn more about new business domains and Technology Innovation\nAn empathetic listener who can give and receive honest thoughtful feedback",
        "word_count": 42
      }
    ],
    "urls": []
  },
  "rejected": false,
  "rejection_reason": null,
  "run_id": "e582ac21-06d8-47c5-b04c-d6ce0e182874",
  "stage3_signals": {
    "alias_match_roles": [
      {
        "display_name": "ML Engineer",
        "matched_count": null,
        "role_id": 3,
        "score": 0.5952,
        "slug": "ml-engineer",
        "total_count": null
      }
    ],
    "kra_match_roles": [
      {
        "display_name": "ML Engineer",
        "matched_count": null,
        "role_id": 3,
        "score": 0.4766,
        "slug": "ml-engineer",
        "total_count": null
      },
      {
        "display_name": "AI Engineer",
        "matched_count": null,
        "role_id": 13,
        "score": 0.4189,
        "slug": "ai-engineer",
        "total_count": null
      },
      {
        "display_name": "Android Engineer",
        "matched_count": null,
        "role_id": 4,
        "score": 0.4141,
        "slug": "android-engineer",
        "total_count": null
      },
      {
        "display_name": "AI Compliance Officer",
        "matched_count": null,
        "role_id": 12,
        "score": 0.4052,
        "slug": "ai-compliance-officer",
        "total_count": null
      },
      {
        "display_name": "Data Engineer",
        "matched_count": null,
        "role_id": 2,
        "score": 0.3867,
        "slug": "data-engineer",
        "total_count": null
      }
    ],
    "skill_match_roles": [
      {
        "display_name": "ML Engineer",
        "matched_count": 4,
        "role_id": 3,
        "score": 0.2222,
        "slug": "ml-engineer",
        "total_count": 18
      },
      {
        "display_name": "Data Engineer",
        "matched_count": 2,
        "role_id": 2,
        "score": 0.1111,
        "slug": "data-engineer",
        "total_count": 18
      },
      {
        "display_name": "Cybersecurity Engineer",
        "matched_count": 2,
        "role_id": 5,
        "score": 0.1111,
        "slug": "cybersecurity-engineer",
        "total_count": 18
      },
      {
        "display_name": "AR/VR Engineer",
        "matched_count": 2,
        "role_id": 8,
        "score": 0.1111,
        "slug": "ar-vr-engineer",
        "total_count": 18
      },
      {
        "display_name": "AI Engineer",
        "matched_count": 2,
        "role_id": 13,
        "score": 0.1111,
        "slug": "ai-engineer",
        "total_count": 18
      }
    ],
    "stage35_ran": false
  },
  "stage4_decision": {
    "alias_collision_detected": false,
    "case": "A",
    "chosen_role": {
      "display_name": "ML Engineer",
      "matched_count": null,
      "role_id": 3,
      "score": 1.0,
      "slug": "ml-engineer",
      "total_count": null
    },
    "confidence": 0.4766,
    "llm2_fired": false,
    "llm2_reasoning": null,
    "queued": false,
    "reasoning": "Stage 1 title \u0027ML Engineer\u0027 (embedding match); KRA agrees (0.48)"
  },
  "stage5_updates": {
    "centroid_n_after": 6,
    "centroid_updated": true,
    "collision_log_id": null,
    "new_kra_attached": null,
    "new_skills_attached": [
      {
        "is_primary": true,
        "queue_id": 560,
        "role_display_name": "ML Engineer",
        "role_slug": "ml-engineer",
        "skill_name": "Machine Learning",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 561,
        "role_display_name": "ML Engineer",
        "role_slug": "ml-engineer",
        "skill_name": "Deep Learning",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 562,
        "role_display_name": "ML Engineer",
        "role_slug": "ml-engineer",
        "skill_name": "Analytics",
        "status": "pending"
      },
      {
        "is_primary": false,
        "queue_id": 563,
        "role_display_name": "ML Engineer",
        "role_slug": "ml-engineer",
        "skill_name": "Caffe",
        "status": "pending"
      },
      {
        "is_primary": false,
        "queue_id": 564,
        "role_display_name": "ML Engineer",
        "role_slug": "ml-engineer",
        "skill_name": "Computer Vision",
        "status": "pending"
      },
      {
        "is_primary": false,
        "queue_id": 565,
        "role_display_name": "ML Engineer",
        "role_slug": "ml-engineer",
        "skill_name": "Natural Language Processing",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 566,
        "role_display_name": "ML Engineer",
        "role_slug": "ml-engineer",
        "skill_name": "Statistics",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 567,
        "role_display_name": "ML Engineer",
        "role_slug": "ml-engineer",
        "skill_name": "Mathematics",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 568,
        "role_display_name": "ML Engineer",
        "role_slug": "ml-engineer",
        "skill_name": "Data Wrangling",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 569,
        "role_display_name": "ML Engineer",
        "role_slug": "ml-engineer",
        "skill_name": "Preprocessing",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 570,
        "role_display_name": "ML Engineer",
        "role_slug": "ml-engineer",
        "skill_name": "Model Testing",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 571,
        "role_display_name": "ML Engineer",
        "role_slug": "ml-engineer",
        "skill_name": "Model Building",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 572,
        "role_display_name": "ML Engineer",
        "role_slug": "ml-engineer",
        "skill_name": "Model Fine-tuning",
        "status": "pending"
      }
    ],
    "queue_entry_id": null,
    "v3_pipeline_triggered": false,
    "v3_role_slug": null,
    "v3_run_id": null
  }
}

API 2 — extract-details

{}

API 3 — final-role-output

{}

LLM Calls

Every model call made for this run, in pipeline order. Click a card to see the model's response.

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