Principal Prediction & Insights Applications Engineer, Small & Large-Molecule Discovery

Working with Us
Challenging. Meaningful. Life-changing. Those aren’t words that are usually associated with a job. But working at Bristol Myers Squibb is anything but usual. Here, uniquely interesting work happens every day, in every department. From optimizing a production line to the latest breakthroughs in cell therapy, this is work that transforms the lives of patients, and the careers of those who do it. You’ll get the chance to grow and thrive through opportunities uncommon in scale and scope, alongside high-achieving teams. Take your career farther than you thought possible.

Bristol Myers Squibb recognizes the importance of balance and flexibility in our work environment. We offer a wide variety of competitive benefits, services and programs that provide our employees with the resources to pursue their goals, both at work and in their personal lives. Read more: careers.bms.com/working-with-us.

Summary:

Own the strategy and delivery of GenAI-native applications, predictive-model workflows, and insight-driven analytics platforms that accelerate large and small-molecule invention. Translate scientific objectives into intuitive software products and robust model-ops practices that help chemists, protein engineers, and data scientists iterate faster, uncover deeper insights, and make better decisions. 

Molecular Discovery ML Enablement: 

• Champion predictive-model use-cases across small and large molecule discovery (e.g., property prediction, sequence optimization, generative design).

• Design and build platforms that orchestrate cutting-edge structure- and sequence-prediction toolkits (RDKit, OpenEye, Schrödinger LiveDesign, AlphaFold) for CADD, sequence design and developability assessment.

• Track, evaluate, and train latest molecular prediction & design models/tools from literature and open-source community. 

AI-Driven Scientific Applications: 

• Using agentic GenAI frameworks, build scientifically grounded conversational analytics, automated reports, and “copilot” workflows that guide scientists through complex SAR, sequence datasets and tools.

• Deliver full-stack applications, React/Next.js fronts with Python/FastAPI & GraphQL services - that surface models and analytics at scale. 

Model-Ops & Engineering Excellence: 

• Stand up automated pipelines for data curation, experiment tracking, CI/CD, and governed model release (PyTorch/TensorFlow + MLflow/Kubeflow/SageMaker + GitHub Actions).

• Package and deploy predictive applications and model endpoints to cloud-native MLOps or on-prem containers for scalable inference and performant access.

• Codify reusable templates, inner-source libraries, and design systems that cut feature time-to-value by 40%. 

Leadership & Collaboration:

• Mentor a cross-disciplinary team of full-stack and ML engineers; foster “better-than-best” practices in code quality, documentation, and UX research.

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