Machine Learning Engineer

About The Role

We are seeking an ML Engineer to build and ship the machine learning and LLM systems behind MMIT's market access intelligence. As one of Norstella's largest global pharma intelligence solution providers, this role sits at the intersection of applied AI engineering and deep domain expertise in life sciences.

Key Responsibilities

• Design, build, and deploy production-ready machine learning and LLM-based models to interpret payer coverage, formulary status, prior authorization requirements, and step therapy rules for commercial teams.
• Tune Large Language Models (LLMs) specifically for market access tasks using fine-tuning, prompt engineering, retrieval augmentation, and parameter optimization. Internalize desired behaviors across edge cases and failure modes.
• Create and refine high-quality datasets consisting of input/output pairs that demonstrate gold-standard behavior in partnership with Market Access Subject Matter Experts (SMEs).
• Run iterative model experiments to diagnose failures, design targeted data or prompt changes, and measure impact using human-in-the-loop feedback from SME graders.
• Build secure AWS SageMaker endpoints, Lambdas, and agentic workflows utilizing Model Context Protocol (MCP) servers for domain-grounded language models.
• Develop robust data pipelines for market access and coverage data feeding training, fine-tuning, and inference workloads using Python libraries like scikit-learn, pandas, Flask/FastAPI.
• Implement MLOps best practices including drift detection, monitoring, troubleshooting, and CI/CD integration (preferably Azure DevOps) to ensure reproducible, auditable, GxP-compliant operations.

Qualifications

Bachelor's or graduate degree in computer science, STEM, life sciences, or equivalent experience. At least 3 years of professional ML engineering experience with a focus on deploying secure models in production.

You will have hands-on experience with Generative AI throughout the SDLC, including LLM tuning (fine-tuning, prompt design), creating MCPs for agentic workflows, and strong Python skills.

Good to Have

• Experience working with US market access data (payer coverage, formulary status, NDCs/J-codes/HCPCS/ICD-10 codes).
• Familiarity with AWS ecosystem beyond SageMaker/Lambda (S3, EC2, ECS, ECR, API Gateway, DynamoDB, Bedrock) or Azure DevOps.
• Knowledge of life sciences data assets like EMRs and clinical trials data.

Benefits

We offer Health Insurance, Provident Fund, Certification Expense Reimbursement, Gratuity, 24x7 Health Desk support, and an inclusive environment where all applicants are treated equally regardless of background. Shift timing is 4PM to 1AM IST.