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ROLE SUMMARY
You will provide independent scientific and strategic leadership for the identification, design, governance, and deployment of artificial intelligence (AI) and advanced analytics solutions across the Vaccines Medical portfolio. You will define a long\-term vision for how AI transforms medical affairs work — including evidence generation, scientific communications, medical content, insights, and field medical enablement — while ensuring that every solution is scientifically rigorous, compliant, and grounded in genuine medical need.
Operating with a high degree of autonomy, you will partner with senior Medical, Development, Digital, Evidence Generation, and cross\-functional leaders to translate enterprise medical priorities into a coherent AI solutions roadmap. Through strategic oversight of AI\-enabled medical solutions, you will ensure that Vaccines Medical adopts trustworthy, future\-ready technology that accelerates scientific work, elevates the quality and consistency of medical outputs, and safeguards scientific integrity — reinforcing Pfizer’s leadership and reputation in vaccines science.
KEY RESPONSIBILITIES
- Define and govern the Vaccines Medical AI strategy and roadmap, integrating input from internal and external stakeholders into long\-term, global planning aligned to Vaccines Global Business Unit and R\&D priorities.
- Serve as a senior scientific and technical advisor to Vaccines Medical leadership, Global Medical franchises, and Global Product Teams, guiding the responsible identification, prioritization, and adoption of high\-impact AI and advanced analytics use cases.
- Establish and govern the frameworks, standards, and controls for responsible AI use — including model validation, human oversight, data provenance, bias monitoring, and documentation — so that solutions are compliant, defensible, and grounded in genuine medical need.
- Define the business case, value framework, and success metrics for AI investments, prioritizing initiatives on measurable medical impact rather than technology for its own sake.
- Lead the design, piloting, and scaled deployment of AI\-enabled solutions that accelerate medical affairs work, such as evidence synthesis and literature surveillance, scientific content generation and review, medical insights aggregation, and field medical support tools.
- Oversee the end\-to\-end delivery lifecycle for prioritized solutions — from use\-case definition and proof\-of\-concept through validation, deployment, adoption, and ongoing performance monitoring — ensuring scientific accuracy and fit\-for\-purpose in a highly regulated environment.
- Partner with Digital and enterprise AI platform teams to influence architecture, data access, and tooling decisions, ensuring solutions are scalable, secure, and interoperable, and represent Vaccines Medical in enterprise AI councils and governance forums.
- Drive change management, training, and capability building so that global, regional, and local Medical Affairs colleagues can adopt AI solutions effectively and responsibly, and adapt centrally developed solutions to local needs.
- Provide senior\-level oversight of financial projections, budget strategy, and resourcing for AI initiatives, including vendor, agency, and offshore team management, ensuring investments demonstrate measurable value.
- Anticipate and interpret evolving US and global regulatory, legal, privacy, and ethical guidance on AI in medical and scientific settings, shaping strategy to ensure compliant, innovative, and future\-ready adoption.
MINIMUM QUALIFICATIONS
- MD and at least 5 years of experience in Medical Affairs, scientific communications, evidence generation, medical or scientific strategy, clinical development, or a related scientific field OR
- PhD and at least 7 years of experience in Medical Affairs, scientific communications, evidence generation, medical or scientific strategy, clinical development, or a related scientific field
- At least 5 years of experience applying artificial intelligence and advanced analytics in scientific or medical settings, including hands\-on experience developing, evaluating, or deploying machine learning, natural language processing, and large language model / generative AI solutions in a life sciences, medical, or scientific context, and their responsible use.
- Experience defining and shaping AI or digital solution strategy — not only executing tactics — including prioritizing use cases, building roadmaps, and translating enterprise medical priorities into high\-impact solutions.
- A comprehensive understanding of Medical Affairs — including medical strategy, evidence generation, scientific communications, and scientific engagement — with the ability to identify where AI creates genuine value, and strong verbal, written, and presentation skills to translate complex concepts into clear narratives.
- Experience operating in a highly regulated environment, with familiarity with the evolving global regulatory and policy landscape governing AI in healthcare and pharmaceutical settings and experience anticipating regulatory, legal, privacy, and ethical considerations and applying responsible, trustworthy AI principles such as model validation, human oversight, data governance, bias mitigation, and transparency.
- Experience overseeing the delivery of technology or analytics solutions from concept through validation, deployment, and sustained adoption, including vendor and partner management, and building credibility across senior, cross\-functional matrix teams.
PREFERRED QUALIFICATION
- Vaccines experience, particularly influencing global medical or scientific strategy across multiple assets or lifecycle stages.
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.
WORK LOCATION ASSIGNMENT: This is a hybrid role requiring you to live within commuting distance and work on\-site an average of 2\.5 days per week
The annual base salary for this position ranges from $214,900\.00 to $358,100\.00\. In addition, this position is eligible for participation in Pfizer’s Global Performance Plan with a bonus target of 22\.5% 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. This role is posted in multiple locations. If you are applying for the role in an secondary job posting location where pay transparency regulations apply, your Talent Advisor will share the local pay information with you during the first interview.
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 [email protected]. 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.
Medical
Salary Context
This $214K-$358K range is above the 75th percentile for AI/ML Engineer roles in our dataset (median: $175K across 2162 roles with salary data).
View full AI/ML Engineer salary data →Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 4,317 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At Pfizer, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills in Demand for This Role
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $214,900 based on 6,420 positions with disclosed compensation. Director-level AI roles across all categories have a median of $274,554. This role's midpoint ($286K) sits 33% above the category median. Disclosed range: $214K to $358K.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
Pfizer AI Hiring
Pfizer has 5 open AI roles right now. They're hiring across AI/ML Engineer. Positions span Pearl River, NY, US, Cambridge, MA, US, New York, NY, US. Compensation range: $207K - $358K.
Location Context
Across all AI roles, 15% (635 positions) offer remote work, while 3,657 require on-site attendance. Top AI hiring metros: New York (1,650 roles, $220,000 median); San Francisco (1,335 roles, $265,000 median); Los Angeles (708 roles, $214,112 median).
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (138) are outnumbered by mid-level (2,071) and senior (1,655) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $287,500 median, while Prompt Engineer roles sit at $145,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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