Senior Principal- AI / ML Engineer, Market Access Intelligence, LVA, Lilly USA Tech
Eli Lilly and Company18 hours ago
Bengaluru, IndiaStaff+
Responsibilities
- Architect and build production-grade machine learning, deep learning, generative AI, and agentic AI systems for market access and engagement use cases.
- Develop RAG, embeddings, semantic search, LLM orchestration, Text2SQL, recommendation, predictive modeling, and workflow automation solutions.
- Design, train, fine-tune, evaluate, and deploy neural network models and production AI services and APIs.
- Own the full AI/ML lifecycle from problem framing and data preparation through deployment, monitoring, and optimization.
- Build scalable data and feature pipelines and implement MLOps/LLMOps practices including experiment tracking, model management, observability, testing, and auditability.
- Apply model distillation, compression, quantization, explainability, responsible AI, privacy, security, and governance practices.
- Collaborate with product, engineering, data science, architecture, compliance, and business stakeholders to translate opportunities into scalable AI capabilities.
- Provide hands-on technical guidance, design reviews, code reviews, and practical mentoring to a small number of engineers.
Requirements
- At least 6 years of experience building and deploying production machine learning or AI solutions.
- At least 3 years of experience with generative AI, including LLMs, RAG, embeddings, prompt engineering, model evaluation, and agentic workflows.
- Strong proficiency in Python and SQL, with hands-on PyTorch experience and TensorFlow preferred.
- Experience with AI/ML frameworks such as PyTorch, TensorFlow, scikit-learn, Hugging Face, LangChain, or DSPy.
- Experience deploying AI services on AWS, Azure, and GCP and implementing MLOps/LLMOps practices.
- Strong software engineering fundamentals, including API development, system design, version control, code reviews, testing, and production deployment.
- Understanding of neural network architectures, transfer learning, model optimization, evaluation, and structured, semi-structured, and unstructured data at scale.
- Preferred experience includes pharma, healthcare analytics, market access, real-world data, payer/formulary data, PySpark, Databricks, SageMaker, Azure ML, multi-agent systems, Text2SQL, semantic search, knowledge graphs, fine-tuning, model optimization, serving frameworks, and responsible AI.
- Preferred education is an M.Tech, MS, or higher in computer science, AI, ML, data science, or a related quantitative discipline.
Tech Stack
AWSAzureDatabricksDockerFastAPIFlaskGitGitHub ActionsGoogle Cloud PlatformKubernetesMLflowPythonPyTorchscikit-learnSQLTensorFlow
Categories
About Eli Lilly and Company
Eli Lilly and Company researches, develops, manufactures, and markets prescription medicines and biologics for patients, sold through healthcare providers, pharmacies, and payers. Core therapeutic areas include diabetes, oncology, immunology, neuroscience, and obesity. Founded in 1876 and headquartered in Indianapolis, it is a public company (NYSE: LLY) with global operations and is building a new advanced manufacturing site for gene therapy and other modalities in Lebanon, Indiana.