Applied AI and Machine Learning Scientist

Pfizer; Cambridge (MA); On-site; USD 180,000 - 250,000; Full time

Job summary

Pfizer is seeking an Applied AI/ML scientist to lead the development and deployment of AI across the Internal Medicine Research Unit (IMRU). The role blends ML, biology, and drug discovery to create reusable AI capabilities, govern AI evaluation, and accelerate evidence generation within AIM2 Discovery Center.

The candidate will guide governance, translate scientific needs into reusable AI solutions, and collaborate with cross-functional teams to ensure scalable, trustworthy AI adoption across

Qualifications

• Advanced degree in computer science, machine learning, computational biology, bioinformatics, statistics, or related field.
• Experience leading complex, cross-functional AI initiatives.
• Hands-on understanding of LLMs and foundation models with ability to guide decisions.

Responsibilities

• Provide AI/ML technical leadership for AIM2 and IMRU.
• Identify high-impact use cases and advance reusable AI capabilities.
• Governance, evaluation, provenance, guardrails for AI-built capabilities.
• Collaborate with internal teams and external partners to align AI efforts with Pfizer priorities.
• Build a culture of scientific rigor, reproducibility, and practical utility.

Skills

LLMs

Foundation models

Generative AI

Machine learning

Technical leadership

Communication

Education

Advanced degree in CS/ML/comp bio/biostatistics or related

5+ years with a Master’s, 6+ with Bachelor’s, or 1+ with PhD

Job description

Role Summary

The successful candidate for the Applied AI/ML scientist position leads the development and application of AI across the Internal Medicine Research Unit (IMRU), translating advances in foundation models, agentic systems, multimodal AI, and related methods into reusable capabilities that strengthen scientific discovery and decision-making. The role combines deep technical credibility with strong scientific judgment and is accountable for shaping the AI portfolio within the newly created AI for IM Discovery (AIM2) Discovery Center within the IMRU, defining governance and evaluation standards, assessing AI/ML capabilities in external (or internal) partnerships, and accelerating practical AI adoption across IMRU. This role is intended for a technically credible AI scientist who can operate at the interface of machine learning, computational biology, and drug discovery, while remaining grounded in the realities of scientific decision-making. Success will require identifying and advancing high-value use cases, leading the development and deployment of scientifically robust AI solutions and building reusable capabilities that improve the speed, quality, and coherence of evidence generation across the portfolio.

Role responsibilities

Provide AI/ML technical leadership for AIM2 by advancing and applying large language models, agentic systems, multimodal AI, and related methods to high value scientific problems across Internal Medicine Research Unit (IMRU) while contributing technical expertise and recommendations that help shape the evolution of AI/ML capabilities in IMRU. Lead the technical evaluation and development of the AI capabilities within the AIM2, working with scientific stakeholders to identify and advance high-impact use cases where technically credible, reusable AI capabilities can create meaningful scientific or operational leverage. Serve as a senior technical and scientific leader across AIM2 Discovery Center, providing expert guidance on the design, evaluation and application of AI/ML approaches to ensure solutions are methodologically sound, fit for purpose, and grounded in biological, translational, and drug discovery context. Lead the design, development and application of reusable AI-enabled capabilities that strengthen scientific decision-making end-to-end, with emphasis on scientific rigor, technical quality, reproducibility, and practical utility across IMRU lines. Contribute technical expertise and best practices for the evaluation standards for AI-built capabilities, including expectations for provenance, validation, guardrails, responsible use, and appropriate human oversight. Partner closely with IMRU Integrative Biology, IMRU line teams, MLCS, and Digital partners to ensure that AI efforts remain tightly aligned to real scientific needs and can be deployed in ways that are trusted, scalable, and adopted in day‑to‑day work. Collaborate with external scientific and technology partners to evaluate external partnerships relevant to AIM2 priorities, providing technical expertise to evaluate emerging technologies and collaborators while ensuring that external engagements remain aligned to Pfizer priorities and IMRU needs. Articulate the value and impact of the AI capabilities to stakeholders across IMRU, providing clear assessments of performance, applicability, limitations and opportunities for broader adoption. Build a strong technical culture within AIM2 and across IMRU, fostering scientific curiosity, high standards, collaboration, and continuous learning, while helping raise confidence in the responsible application of AI across IMRU.

BASIC QUALIFICATIONS

• Advanced degree in computer science, machine learning, artificial intelligence, computational biology, bioinformatics, statistics, engineering, life sciences, or a related quantitative or scientific field preferred.
• Typically, candidates at this level will bring substantial relevant experience, for example approximately 5+ years with a Master’s degree, 6+ years with a Bachelor’s degree, or 1+ years with a PhD, while recognizing that the right mix of scope, technical depth, scientific credibility, and impact matters more than degree alone.
• Demonstrated experience leading complex, cross‑functional initiatives in applied AI, computational science, data science, digital transformation, or related domains, ideally with responsibility for developing innovative solutions and delivering measurable scientific, technical or operational impact.
• Strong hands‑on understanding of LLMs, foundation models, generative AI, machine learning, and related AI approaches, with the technical credibility to guide decisions, assess trade‑offs, and challenge weak approaches even when not serving as the primary builder.
• Demonstrated ability to identify and advance scientific applications of AI in ambiguous environments, translating scientific or stakeholder needs into practical, reusable solutions with measurable impact.
• Experience building and scaling reusable workflows, methods, products, or platforms rather than delivering isolated one‑off analyses.
• Demonstrated ability to provide technical thought leadership in AL/ML, communicate complex concepts to scientific and business audiences, and influence decision‑making through data, evidence and technical expertise.
• Strong matrix leadership, communication, and influence skills, including the ability to align senior stakeholders, provide technical direction, and drive adoption without relying solely on formal authority.
• Sound judgment regarding methodological rigor, evaluation, provenance, model limitations, risk, and the appropriate role of human oversight in AI‑enabled scientific workflows.

PREFERRED QUALIFICATIONS

• Experience in life sciences, pharma, biotech, translational science, omics, or related research environments.
• Experience and/or training in cardiovascular, metabolic, or obesity biology.
• Demonstrated ability to operate fluently across AI / technology and biology, grounding technical solutions in scientific reality and engaging credibly with scientists and line leaders.
• Experience with AI adoption, productization, governance, or workflow transformation in complex, matrixed, regulated