AI/ML Engineer

Senior AI/ML + MLOps Engineer Experience: 6–10+ years Location: As per project requirement (Global Pharma & Healthcare)---Role SummaryCapgemini 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.---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 Sanofi’s 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 AWS—SageMaker, 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 ---Required Skills· Expert Python & advanced ML/LLM engineering experience.· Strong expertise in APIs, integration architecture, REST frameworks, security tokens.· Strong orchestration expertise—Airflow / 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.---Good to Have · Pharma/healthcare domain experience.· Understanding of HIPAA/GxP/GDPR compliance.· Knowledge of lab workflows, R&D processes, scientific data systems.

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