Machine Learning Scientist Jobs in Massachusetts

Applied AI and Machine Learning Scientist (Director)

• United States - Massachusetts - Cambridge

We’re in relentless pursuit of breakthroughs that change patients’ lives. We innovate every day to make the world a healthier place.

To fully realize Pfizer’s purpose – Breakthroughs that change patients’ lives – we have established a clear set of expectations regarding “what” we need to achieve for patients and “how” we will go about achieving those goals.

Pfizer Research & Development serves as the beating heart of Pfizer's trailblazing product pipeline, the essence of our mission to bring life-changing medicines to the world.

Pfizer offers competitive compensation and benefits programs designed to meet the diverse needs of our colleagues.

The successful candidate for the Applied AI / ML scientist position leads the technical evaluation, 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 decision-making end-to-end. 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 leader 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 setting a clear strategy, directing high-value use cases, ensuring that solutions and partnerships are scientifically robust and trusted, 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 and define a clear roadmap for how large language models, agentic systems, multimodal AI, and related methods will be applied to high-value scientific problems across Internal Medicine Research Unit (IMRU).
• Lead the technical evaluation and development of the AI capabilities in the AIM2, identifying, prioritizing, and shaping opportunities so that AIM2 focuses on areas where technically credible, reusable AI capabilities can create meaningful scientific or operational leverage.
• Provide senior technical and scientific direction across AIM2 Discovery Center, ensuring that proposed solutions are methodologically sound, fit for purpose, and grounded in biological, translational, and drug discovery context.
• Guide the development 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.
• Establish governance and 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.
• Shape and manage selected external partnerships relevant to AIM2 priorities, helping 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 within IMRU to senior stakeholders, including technical differentiation, adoption trajectory, and return on investment of key initiatives to support strategic planning and decision making
• 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 9+ years with a Master’s degree, 10+ years with a Bachelor’s degree, or 7+ 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 strategy, portfolio prioritization, and value realization.
• 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, prioritize, and shape high‑value use cases 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 develop strategy, shape AI portfolios, and communicate impact and return on investment to senior stakeholders in a clear and credible way.
• Strong matrix leadership, communication, and influence skills, including the ability to align senior stakeholders, provide technical and strategic 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 organizations.
• Familiarity with scientific evidence synthesis, literature and document workflows, retrieval‑augmented approaches, multimodal AI, or agentic systems applied to scientific problems.
• Experience working with external technology partners, vendors, or academic collaborators to evaluate, shape, or deploy AI capabilities.
• Evidence of an entrepreneurial, product‑minded approach, including spotting opportunities, making pragmatic trade‑offs, iterating rapidly, and turning promising concepts into durable capabilities that are reused and adopted.

ORGANIZATIONAL RELATIONSHIPS

Director of AIM2; AIM2 Innovation Fellows; CSO IMRU; Head of IMRU Integrative Biology; Integrative Biology Scientists; IMRU biology line teams; Integrative Biology and Digital ecosystem partners; AI/ML practitioners, computational biologists, translational scientists, portfolio and strategy stakeholders, and other leaders involved in AI prioritization, deployment, governance, and adoption.

External:

May interact, as appropriate, with external technology partners, vendors, or academic / industry collaborators relevant to AI capability evaluation, development, and adoption.

Candidate demonstrates a breadth of diverse leadership experiences and capabilities including: the ability to influence and collaborate with peers, develop and coach others, oversee and guide the work of other colleagues to achieve meaningful outcomes and create business impact.

This is a hybrid role requiring you to live within commuting distance and work on‑site an average of 2.5 days per week.

#LI-PFE

The annual base salary for this position ranges from $176,600.00 to $294,300.00. In addition, this position is eligible for participation in Pfizer’s Global Performance Plan with a bonus target of 20.0% of the base salary and eligibility to participate in our share based long term incentive program. We offer comprehensive and generous benefits and programs to help our colleagues lead healthy lives and to support each of life’s moments. Benefits offered include a 401(k) plan with Pfizer Matching Contributions and an additional Pfizer Retirement Savings Contribution, paid vacation, holiday and personal days, paid caregiver/parental and medical leave, and health benefits to include medical, prescription drug, dental and vision coverage. Learn more at Pfizer Candidate Site – U.S. Benefits | (uscandidates.mypfizerbenefits.com). Pfizer compensation structures and benefit packages are aligned based on the location of hire. The United States salary range provided does not apply to Tampa, FL or any location outside of the United States.

Relocation assistance may be available based on business needs and/or eligibility.

Candidates must be authorized to be employed in the U.S. by any employer.

U.S. work visa sponsorship (such as TN, O-1, H-1B, etc.) is not available for this role now or in the future.

Sunshine Act

Pfizer reports payments and other transfers of value to health care providers as required by federal and state transparency laws and implementing regulations. These laws and regulations require Pfizer to provide government agencies with information such as a health care provider’s name, address and the type of payments or other value received, generally for public disclosure. Subject to further legal review and statutory or regulatory clarification, which Pfizer intends to pursue, reimbursement of recruiting expenses for licensed physicians may constitute a reportable transfer of value under the federal transparency law commonly known as the Sunshine Act. Therefore, if you are a licensed physician who incurs recruiting expenses as a result of interviewing with Pfizer that we pay or reimburse, your name, address and the amount of payments made currently will be reported to the government. If you have questions regarding this matter, please do not hesitate to contact your Talent Acquisition representative.

EEO & Employment Eligibility

Pfizer is committed to equal opportunity in the terms and conditions of employment for all employees and job applicants without regard to race, color, religion, sex, sexual orientation, age, gender identity or gender expression, national origin, disability or veteran status. Pfizer also complies with all applicable national, state and local laws governing nondiscrimination in employment as well as work authorization and employment eligibility verification requirements of the Immigration and Nationality Act and IRCA. Pfizer is an E-Verify employer. This position requires permanent work authorization in the United States.

Pfizer endeavors to make www.pfizer.com/careers accessible to all users. If you would like to contact us regarding the accessibility of our website or need assistance completing the application process and/or interviewing, please email disabilityrecruitment@pfizer.com . This is to be used solely for accommodation requests with respect to the accessibility of our website, online application process and/or interviewing. Requests for any other reason will not be returned.

To learn more about acceptable and prohibited uses of AI during the recruitment process, please review our candidate AI-use guidelines available on Pfizer Careers.

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