AI/ML Engineer

Senior AI/ML + MLOps Engineer

Experience: 610+ years Location: As per project requirement (Global Pharma & Healthcare)

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Role Summary

Capgemini is looking for a Senior AI/ML + MLOps Engineer with strong integration expertise to lead complex ML systems This role demands deep hands-on knowledge in model training, LLM fine-tuning using PEFT, API-based integration design, orchestration workflows, and end-to-end MLOps automation compliant with pharma regulations.

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Key Responsibilities

Architect and lead ML, LLM, and AI platform solutions end-to-end.

Execute and optimize PEFT-based fine-tuning pipelines for LoRA/QLoRA.

Design and manage API-driven integrations with Sanofis internal and external systems.

Build orchestration workflows using Airflow, Step Functions, Argo, or similar.

Lead the implementation of robust MLOps pipelines (training, CI/CD, deployment, monitoring).

Implement model governance, experiment tracking, reproducibility, and audit compliance.

Deploy ML models on AWSSageMaker, EKS/ECS, Lambda, Step Functions.

Ensure alignment with DMTA cycle, supporting cross-functional teams through Design Make Test Analyze.

Ensure adherence to pharma-grade security, compliance, and data privacy requirements.

Mentor junior engineers and coordinate solution design

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Required Skills

Expert Python & advanced ML/LLM engineering experience.

Strong expertise in APIs, integration architecture, REST frameworks, security tokens.

Strong orchestration expertiseAirflow / Step Functions / Kubeflow / Prefect.

In-depth understanding of DMTA lifecycle in scientific workflows.

Advanced MLOps skills (MLflow, DVC, Kubeflow, Docker, Kubernetes).

Strong AWS hands-on experience including SageMaker pipelines.

Experience in GPU optimization, distributed training, quantization.

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Good to Have

Pharma/healthcare domain experience.

Understanding of HIPAA/GxP/GDPR compliance.

Knowledge of lab workflows, R&D processes, scientific data systems.