Scientist, Predictive Biology and AI at Bristol Myers Squibb Cambridge, MA
Listed on 2026-07-24
-
Software Development
AI Engineer (Applied/Software), Data Scientist, Machine Learning/ ML Engineer
Bristol-Myers Squibb – Scientist, Predictive Biology and AI
Location:
Cambridge, MA; other locations available:
Seattle, WA;
Brisbane, CA;
San Diego, CA;
Princeton, NJ.
Scientific research and AI development in oncology and neuroscience.
The Predictive Biology and AI (PBAI) team within BMS Research develops and applies cutting‑edge methods to address patient needs and answer fundamental questions in oncology, neuroscience, and other application areas. The role works closely with wet‑lab partners to test and deliver predictions into the pipeline and integrate data generated into models. The successful candidate will adapt state‑of‑the‑art AI models to challenges in cell engineering and target discovery, directly impacting life‑changing therapies.
Responsibilities- Apply, adapt, and in some cases create multi‑modal foundation models such as LLMs, diffusion models, and encoder architectures to answer biological domain‑specific questions.
- Address real‑world biological modeling challenges such as data sparsity, class imbalance, noise, experimental bias, and heterogeneity of effects.
- Perform thoughtful model evaluation that incorporates appropriate benchmarks, statistical tests, and problem understanding to support technical and business decisions.
- Collaborate with wet‑lab scientists, Research IT, and other computational scientists to broaden the impact of AI developments.
- Maintain and share up‑to‑date knowledge of modern advances in the field, including presenting work at public conferences.
- Bachelor’s degree + 5+ years of academic/industry experience.
- Master’s degree + 3+ years of academic/industry experience.
- Ph.D. with no required experience.
- Ph.D. with 0+ years of industry research experience or M.S. with 3+ years of industry research experience in computer science, statistics, computational biology, or another quantitative field.
- Expert‑level understanding of and experience using deep learning tools and approaches (transformer‑based encoders/decoders, LLMs, reinforcement learning, etc.) as demonstrated through publications or projects.
- Hands‑on experience leading the building and scaling of deep learning training pipelines on multi‑GPU computational infrastructure using PyTorch, Huggingface, and/or other tools.
- Knowledge of or ability to learn biological concepts and data types, and ability to work and communicate effectively with biologists.
- Excellent verbal and written communication skills; fluent in English.
- Experience building agentic workflows is a plus.
- Prior experience in pharmaceutical application areas is a plus.
- Brisbane, CA – $141,150 – $171,042
- Cambridge, MA – $141,150 – $171,042
- Princeton, NJ – $122,740 – $148,732
- San Diego, CA – $135,010 – $163,605
- Seattle, WA – $135,010 – $163,605
- Medical, pharmacy, dental and vision care.
- Well‑being support programs, employee assistance.
- Financial well‑being resources, 401(k) plan.
- Insurance: short‑term and long‑term disability, life insurance, supplemental health, business travel protection, survivor support.
- Paid national holidays, optional holidays, up to 120 hours of paid vacation, voluntary days, sick time, summer hours flexibility.
- Parental, caregiver, bereavement, and military leave.
- Family care services including adoption and surrogacy reimbursement, fertility benefits, support for traveling mothers, child, elder and pet care resources.
- Tuition reimbursement and recognition program.
Bristol-Myers Squibb is an equal‑opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, protected veteran status, pregnancy, citizenship, marital status, gender expression, genetic information, political affiliation, or any other characteristic protected by law.
#J-18808-Ljbffr(If this job is in fact in your jurisdiction, then you may be using a Proxy or VPN to access this site, and to progress further, you should change your connectivity to another mobile device or PC).