Bristol Myers Squibb
Principal AI Engineer (GenAI) - Molecular Discovery
Bristol Myers Squibb, Princeton, New Jersey, us, 08543
Overview
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Principal AI Engineer (GenAI) - Molecular Discovery
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Bristol Myers Squibb . Summary
Own the strategy and delivery of Gen AI-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 best practices in code quality, documentation, and UX research. Partner with discovery leads, IT operations, and external vendors to align technical backlogs with portfolio milestones and data-quality standards. Influence budgeting and make-vs-buy decisions for AI tooling and platform enhancements. Qualifications
Deep Discovery & Molecular Tooling Context – 7+ years with relevant advanced degree building/supporting platforms and tools for computational compound design and protein engineering workflows (Schrödinger, OpenEye, MOE, MIXCR, AlphaFold); fluent in SAR analysis, sequence/structure predictions, and assay lifecycles. GenAI engineering depth – Demonstrated success building GenAI applications and agentic workflows; fine-tuning and deploying LLMs, diffusion models, structure-prediction models (AlphaFold family, RoseTTAFold), or vision transformers for scientific or operational use-cases. Modern MLOps – IaC (Terraform/CloudFormation), automated testing, secrets management, continuous model evaluation, lineage tracking. Influence & communication – lead architecture reviews, map tech choices to scientific KPIs, mentor cross-functional teams, and guide roadmap workshops with executives and bench scientists alike. Education / Credentials
M.S. or Ph.D. in Computer Science, Machine Learning, Computational Chemistry/Biology, or related field; Cloud-architect certification a plus. Join Us Empower researchers with the AI tools, agentic workflows, and insight-driven applications they need to invent the next generation of therapeutics - faster, smarter, and at scale. The starting compensation for this job is a range from $155,000 - $170,000, plus incentive cash and stock opportunities (based on eligibility). Final, individual compensation will be decided based on demonstrated experience. Eligibility for specific benefits listed on our careers site may vary based on the job and location. For more on benefits, please visit https://careers.bms.com/life-at-bms/. BMS is an equal employment opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, or veteran status. Reasonable accommodations may be provided in the recruitment process per applicable laws.
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Join to apply for the
Principal AI Engineer (GenAI) - Molecular Discovery
role at
Bristol Myers Squibb . Summary
Own the strategy and delivery of Gen AI-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 best practices in code quality, documentation, and UX research. Partner with discovery leads, IT operations, and external vendors to align technical backlogs with portfolio milestones and data-quality standards. Influence budgeting and make-vs-buy decisions for AI tooling and platform enhancements. Qualifications
Deep Discovery & Molecular Tooling Context – 7+ years with relevant advanced degree building/supporting platforms and tools for computational compound design and protein engineering workflows (Schrödinger, OpenEye, MOE, MIXCR, AlphaFold); fluent in SAR analysis, sequence/structure predictions, and assay lifecycles. GenAI engineering depth – Demonstrated success building GenAI applications and agentic workflows; fine-tuning and deploying LLMs, diffusion models, structure-prediction models (AlphaFold family, RoseTTAFold), or vision transformers for scientific or operational use-cases. Modern MLOps – IaC (Terraform/CloudFormation), automated testing, secrets management, continuous model evaluation, lineage tracking. Influence & communication – lead architecture reviews, map tech choices to scientific KPIs, mentor cross-functional teams, and guide roadmap workshops with executives and bench scientists alike. Education / Credentials
M.S. or Ph.D. in Computer Science, Machine Learning, Computational Chemistry/Biology, or related field; Cloud-architect certification a plus. Join Us Empower researchers with the AI tools, agentic workflows, and insight-driven applications they need to invent the next generation of therapeutics - faster, smarter, and at scale. The starting compensation for this job is a range from $155,000 - $170,000, plus incentive cash and stock opportunities (based on eligibility). Final, individual compensation will be decided based on demonstrated experience. Eligibility for specific benefits listed on our careers site may vary based on the job and location. For more on benefits, please visit https://careers.bms.com/life-at-bms/. BMS is an equal employment opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, or veteran status. Reasonable accommodations may be provided in the recruitment process per applicable laws.
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