Hybrid Principal AI Engineer – Molecular Discovery

at Bristol Myers Squibb

• Job title: Principal AI Engineer – Molecular Discovery
• Job type: Full Time
• Experience level: Lead
• Salary: $158,870 - $211,758 per year
• Degree requirement: Postgraduate Degree
• Tech skills: Cloud, GraphQL, JavaScript, Next.js, Python, PyTorch, React, Tensorflow, Terraform
• Location requirements: Hybrid, Princeton, United States

About the role

• Principal AI Engineer creating GenAI-native applications for bioengineering and predictive-model workflows. Translating scientific objectives into intuitive software products enhancing discovery efficiency.

Responsibilities

• Own the strategy and delivery of GenAI-native applications, predictive-model workflows, and insight-driven analytics platforms that accelerate both small-molecule and biotherapeutic 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.
• Champion predictive-model use-cases across medicinal chemistry and biologics (e.g., property prediction, sequence optimization, generative design).
• Harness cutting-edge structure- and sequence-prediction models (AlphaFold/OpenFold, RoseTTAFold, RFdiffusion, Schrodinger, OpenEye) to accelerate target triage, protein engineering, and binding-interface analysis.
• Track, evaluate, and train molecular prediction models and integrate genAI methods in the literature and open-source community.
• Ensure model outputs, metrics, and explainability align with discovery KPIs and downstream lab workflows.
• Integrate agentic genAI frameworks (e.g., Bedrock, LangChain, LlamaIndex, AzureOpenAI) to create conversational analytics, automated report writers, and “copilot” agents that guide scientists through complex SAR, sequence, or imaging datasets.
• Deliver full-stack applications—React/Next.js fronts with Python/FastAPI & GraphQL services—that surface models and analytics at scale with sub-second responsiveness.
• 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 PaaS 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%.
• Mentor a cross-disciplinary team of full-stack and ML engineers; foster “better-than-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.

Requirements

• Deep Discovery Context – 8-10 yrs building software or ML solutions for medicinal chemistry, biologics engineering, or high-content screening; fluent in SAR data, sequence/structure relationships, and assay lifecycles.
• Molecular Tooling Familiarity - Practical mastery of open-source and proprietary molecular-design toolkits (e.g., EvoDiff, RFdiffusion, Molformer, RDKit, Alphfafold, Schrodinger, OpenEye) and the ability to integrate or adapt them within proprietary pipelines.
• Hands-on GenAI / ML depth – Demonstrated success fine-tuning and deploying LLMs, diffusion models, GNNs, structure-prediction models (AlphaFold family, RoseTTAFold, ESMFold), 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.

Benefits

• Medical, pharmacy, dental and vision care.
• Wellbeing support such as the BMS Living Life Better program and employee assistance programs (EAP).
• Financial well-being resources and a 401(K).
• Financial protection benefits such as short- and long-term disability, life insurance, supplemental health insurance, business travel protection and survivor support.
• Work-life programs include paid national holidays and optional holidays, Global Shutdown Days between Christmas and New Year’s holiday, up to 120 hours of paid vacation, up to two (2) paid days to volunteer, sick time off, and summer hours flexibility.
• Parental, caregiver, bereavement, and military leave.
• Family care services such as adoption and surrogacy reimbursement, fertility/infertility benefits, support for traveling mothers, and child, elder and pet care resources.
• Other perks like tuition reimbursement and a recognition program.