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Manager - Foundation Model(Model Evaluation & MLOps)

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Onsite

Manager - Foundation Model(Model Evaluation & MLOps)

National Institute for Smart Government (NISG)

Manager - Foundation Model(Model Evaluation & MLOps)

Skills

DockerData ScienceData AnalysisMachine LearningAIKubernetes

1 month ago

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Important information


Contract type:

Permanent

Location:

Delhi, India

Work mode:

Onsite

Published on:

9 September 2026

What they need


Position: Manager Foundation Model (Model Evaluation & MLOps)
Experience: 6+ Years

Role Overview

We are looking for a Manager to support Foundation Model initiatives across model evaluation, benchmarking, MLOps, deployment readiness, compute utilisation and technical programme tracking.

Key Responsibilities

  • Coordinate AI/ML model evaluation, testing and benchmarking activities.
  • Track model performance, quality, safety, robustness and efficiency metrics.
  • Monitor the AI/ML lifecycle from training and fine-tuning to deployment and monitoring.
  • Track MLOps activities including model versioning, experiment tracking, deployment and monitoring.
  • Review cloud/GPU/TPU compute utilisation, infrastructure requirements and cost efficiency.
  • Coordinate with startups, technology partners and technical teams for timely delivery.
  • Prepare technical MIS, dashboards, evaluation reports and management updates.
  • Identify performance gaps, deployment risks, infrastructure bottlenecks and technical dependencies.

Education

B.E./B.Tech/M.Tech/MCA/MBA in Computer Science, IT, AI/ML, Data Science, Electronics, Computer Engineering, Software Engineering, Business Analytics or related discipline from a recognised University/Institution.

Required Skills & Experience

  • 6+ years of experience in AI/ML, Data Science, MLOps, ML Engineering, Cloud/AI Infrastructure, Software Systems or Technical Programme Management.
  • Strong understanding of AI/ML lifecycle, model evaluation, benchmarking, deployment and monitoring.
  • Familiarity with one or more of Git, MLflow, Weights & Biases, Docker, Kubernetes, CI/CD, APIs or Cloud Platforms.
  • Exposure to GPU/TPU/HPC or AI compute environments is desirable.
  • Strong analytical, coordination, documentation and stakeholder management skills.

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