PD Senior Engineer – Model Lifecycle, Sustainability and MLOps, Pharmaceutical Product Development
Bristol Myers Squibb (company site, opens in a new tab)4+ yrsHyderabadOn-siteDirect career pageEst. 18–30 LPA
Posted on 9 Sept
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Job description
Structured overview of role & requirements
About This Role
- Drive the model lifecycle sustainability efforts for machine learning and data-driven models within Pharmaceutical Product Development, ensuring reproducibility, observability, governance, and value after deployment.
- Develop and implement MLOps frameworks, deployment, monitoring, and continuous improvement workflows for advanced models across manufacturing, product performance, and analytics.
- Build scalable model discoverability, governance standards, and monitoring strategies including alerting for model performance, data drift, and infrastructure health to support model reuse across programs.
Minimum Requirements
- Bachelor's degree in Computer Science, Engineering, Statistics, Data Science or related discipline.
- At least 4 years industry experience with MLOps including Git, CI/CD, automated testing, model registries, experiment tracking, observability, versioning, and governance.
- Hands-on experience with Databricks, AWS, MLflow, Docker, Kubernetes, GitHub Actions, Azure DevOps, Lakehouse Monitoring, Evidently AI.
- Strong expertise in Python, PySpark, and knowledge of machine learning libraries such as scikit-learn and PyTorch.
Ideal Candidate Profile
- Experienced in deploying, operating, monitoring, and maintaining production ML solutions through multiple lifecycle stages in regulated, scientific environments.
- Able to translate complex scientific and technical needs into scalable platform capabilities and adoption roadmaps, balancing rigor, engineering quality, and practical business outcomes.
- Skilled at engaging diverse stakeholders across scientific, engineering, product, and governance teams and driving alignment on technical standards and lifecycle practices.