Machine Learning Engineer

About BI&A and the AI Engineering Team

The Lilly Bengaluru Business Insights & Analytics (BI&A) team was started in 2017 with the objective of using innovative data mining and analytics to support business decisions for Marketing functions in the US and ex-US affiliates. The team has grown to more than 100 staff members across data management, data science, analytical techniques, pharmaceutical commercial operations, and business insights, and provides analytics outcomes that drive decision-making across Lilly's Marketing, Sales, Medical Affairs, and other functions. A parallel data and analytics team operates out of Indianapolis (HQ).

Within BI&A, the AI Engineering team designs, builds, and operates the platforms that take Lilly's commercial generative-AI and agentic-AI solutions from prototype to enterprise-scale production — including our agentic AI application platform and its transition to a modern, cloud-hosted architecture, and BI&A's participation in Lilly's broader enterprise agentic AI platform initiative.

Role Overview

We are looking for a Machine Learning Engineer to join the AI Engineering team, with a primary focus on Hands-On Engineering (MLE) and MLOps & Platform Reliability.

Core Responsibilities

• Build and maintain production-grade ML/AI components and services with minimal supervision.

• Apply software engineering best practices (version control, testing, code review, documentation) across your work.

• Debug and resolve moderately complex issues spanning multiple components of the system.

• Take ownership of small features or workstreams end-to-end, from design through deployment.

• Build and maintain CI/CD pipelines (e.g. GitHub Actions) for ML/AI deployments; contribute to pipeline design for new projects.

• Work with Docker, Kubernetes, and Prefect to deploy and orchestrate ML/AI workloads across environments.

• Support models through deployment, monitoring, and retraining; escalate drift or degradation issues.

Key Tools & Technologies

• Cloud & Data Infra: AWS (EC2/ECS, S3, Lambda, IAM, CloudWatch or equivalent); Databricks & Unity Catalog

• Foundational: Python; Git/GitHub; software engineering best practices; testing; SQL

• MLOps & Deployment: Docker, Kubernetes, Prefect; CI/CD (GitHub Actions); production monitoring; model versioning & lineage; GitOps governance

Required Qualifications

• 0–4 years of hands-on experience building and operating ML/AI systems in production environments.

• Strong proficiency in Python and a track record of writing clean, testable, production-quality code.

• Demonstrated experience owning CI/CD, containerisation, and orchestration for production ML/AI systems.

• Strong working knowledge of containerisation (Docker), orchestration (Kubernetes), and CI/CD pipelines.

• Working knowledge of AWS cloud services and Databricks/Unity Catalog or equivalent enterprise data platforms.

• Excellent verbal and written communication skills.

• Experience working in Agile/Scrum environments.

Education

• Bachelor's or Master's degree in Computer Science, Computer Applications, or a related technical field.

Lilly is dedicated to helping individuals with disabilities to actively engage in the workforce, ensuring equal opportunities when vying for positions. If you require accommodation to submit a resume for a position at Lilly, please complete the accommodation request form (https://careers.lilly.com/us/en/workplace-accommodation) for further assistance. Please note this is for individuals to request an accommodation as part of the application process and any other correspondence will not receive a response.

Lilly does not discriminate on the basis of age, race, color, religion, gender, sexual orientation, gender identity, gender expression, national origin, protected veteran status, disability or any other legally protected status.

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