5 days ago
Cambridge, MA, USASenior
Base Salary
$139k - $232k/yr
Responsibilities
- Design and build fit-for-purpose AI/ML systems for recurring scientific and clinical workflows, including hybrid RAG systems.
- Evaluate, debug, and rebuild AI-assisted prototypes to address technical and scientific failure modes before wider deployment.
- Build data platforms, ETL pipelines, database foundations, cloud deployments, and evaluation harnesses for internal AI tools.
- Own promotion of tools from alpha to beta and define production-readiness standards, guardrails, documentation, and human oversight.
- Run scientific and clinical evaluation loops with computational biologists, immunologists, biologists, and clinicians.
- Evaluate commercial AI/ML and GenAI tools and vendors to support build-versus-buy and purchasing decisions.
- Create SOPs, hardened primitives, reference architectures, and benchmark harnesses that scale across deployments.
- Stay current on translational AI methods and contribute through conferences, publications, and technical presentations.
- Influence, coach, and guide colleagues while contributing to a rigorous and collaborative engineering culture.
Requirements
- PhD with 1+ years of experience, or a master's degree with 5+ years of software or ML engineering experience, or a bachelor's degree with 6+ years of experience and/or equivalent demonstrated experience shipping AI/ML systems for scientific applications.
- Hands-on experience building AI/ML systems beyond prompt-wrapping, with depth in generative AI, agentic workflows, predictive models, foundation models, hybrid RAG, or fine-tuned architectures.
- Strong Python engineering skills and fluency with modern AI/ML tools, model APIs, prompt engineering, fine-tuning, predictive modeling, evaluation tooling, and frameworks such as PyTorch, HuggingFace, LangChain, or LlamaIndex.
- Experience building database and ETL foundations, including Postgres or an equivalent database.
- Hands-on cloud infrastructure and deployment experience with AWS, GCP, or Azure, containerization, and CI/CD patterns.
- Sufficient immunology, biology, translational research, or clinical workflow literacy to understand partner needs.
- Demonstrated experience building evaluation harnesses, performing error analysis, hardening systems, and making build-versus-buy decisions.
- Experience delivering in evolving environments and making deliberate engineering tradeoffs when speed could create production risk.
- Preferred experience includes TypeScript and React, scientific or clinical data, immunology or biotech R&D, multi-omics, biological foundation models, production enterprise software, security and compliance requirements, and a strong open-source or publication record.
- Ability to influence and collaborate with peers, develop and coach others, and guide colleagues toward meaningful outcomes.
Benefits
- Hybrid work arrangement requiring residence within commuting distance and on-site work an average of 2.5 days per week.
- Comprehensive benefits including a 401(k) plan with matching contributions, an additional retirement savings contribution, paid vacation, holidays and personal days, caregiver/parental and medical leave, and medical, prescription drug, dental, and vision coverage.
- Eligibility for Pfizer's Global Performance Plan and share-based long-term incentive program.
- Relocation assistance may be available based on business needs and eligibility.
- Applications are accepted through September 16, 2026.
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