Senior Machine Learning Engineer
Eli Lilly and CompanyMatch Score
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Protocol Intelligence
Data-driven signals on your job's competitivenessTier-1 pharma brand, mid-level ML role in Bengaluru with broad MLOps requirements increases applicant competition.
MLOps and engineering skills transfer well across industries, though pharma domain knowledge is advantageous.
Explicit 4–8 years plus mandatory MLOps, cloud, containerization, and CI/CD requirements produce high shortlisting strictness.
Job Description
Structured overview of role & requirementsAbout This Role
Build and maintain production-grade ML/AI components and services with minimal supervision, owning features end-to-end from design to deployment.
Develop and maintain CI/CD pipelines for ML/AI deployments using tools like GitHub Actions, Docker, Kubernetes, and Prefect.
Support ML models through deployment, monitoring, retraining, and escalation of performance issues such as drift or degradation.
Minimum Requirements
4–8 years of hands-on experience building and operating ML/AI systems in production environments.
Strong proficiency in Python and/or R with proven clean, testable, production-quality coding skills.
Experience with CI/CD, containerization (Docker), orchestration (Kubernetes), and cloud services (AWS, Databricks/Unity Catalog or equivalents).
Bachelor's or Master's degree in Computer Science, Computer Applications, or related technical field.
Ideal Candidate Profile
Experienced in applying software engineering best practices across ML/AI systems in production environments operating at enterprise scale.
Comfortable working in Agile/Scrum environments and owning multiple components or features with accountability for reliability and platform scalability.
Strong knowledge of cloud infrastructure and modern MLOps tools, emphasizing platform reliability and automation for ML/AI workloads.