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About the Role

Pfizer is building a new AI-native operating model where small, highly capable teams combine human expertise with AI to achieve outcomes at an unprecedented pace. This role is crucial in inventing and championing this model, rethinking work organization, problem decomposition, delegation to intelligent systems, and human-AI collaboration for fundamental transformation.

Responsibilities

Own critical AI capabilities from architecture through production deployment.
Lead the design and delivery of end-to-end systems that directly enable scientific discovery.
Design, develop, and deploy production-grade AI systems supporting multimodal biomedical models and intelligent agents.
Engineer data pipelines, retrieval systems, evaluation frameworks, knowledge systems, inference services, and human-in-the-loop workflows.
Create scalable software that enables AI capabilities to move beyond experimentation and into everyday scientific use.
Translate scientific and business needs into technical solutions.
Lead architecture, implementation, testing, deployment, monitoring, and continuous improvement for your area of ownership.
Drive projects from concept through production and operational support.
Partner closely with AI scientists, computational biologists, data engineers, and platform teams.
Transform promising prototypes into reusable, reliable, and maintainable systems.
Develop solutions with clear interfaces, measurable performance, and long-term sustainability.
Balance performance, scalability, cost, reliability, security, privacy, maintainability, and speed of delivery.
Apply sound engineering judgment when evaluating technical approaches and system architecture decisions.
Strengthen model evaluation, observability, reproducibility, lineage, security, and operational resilience.
Implement practices that support responsible and trustworthy AI deployment within scientific environments.
Contribute to architecture reviews, code reviews, engineering standards, and reusable technical patterns.
Troubleshoot complex problems and improve engineering quality across the organization.
Provide guidance and support to less-experienced engineers through collaboration and mentorship.
Define success metrics and operational indicators.
Continuously improve performance, reliability, usability, and scientific impact.
Help teams adopt AI with confidence and scale.

Requirements

PhD in Computer Science, Computer Engineering, Electrical Engineering, Applied Mathematics, or a related technical discipline with demonstrated experience building software, systems, or machine learning solutions; OR Master's degree with 2+ years of relevant experience; OR Bachelor's degree with 4+ years of relevant experience.
Demonstrated experience designing and delivering production software or machine learning systems.
Demonstrated experience owning technical solutions from architecture through deployment.
Demonstrated experience building reliable systems in cloud, distributed computing, or HPC environments.
Demonstrated experience developing maintainable, testable, and scalable software.
Strong proficiency in Python software development.
Strong proficiency in modern machine learning frameworks such as PyTorch or JAX.
Strong proficiency in software architecture and system design.
Strong proficiency in APIs, testing, debugging, version control, and technical documentation.
Strong proficiency in containers, orchestration, CI/CD, and deployment workflows.
Proven ability to work effectively across interdisciplinary teams.
Proven ability to navigate ambiguity and solve complex problems.
Proven ability to communicate technical concepts to broad audiences.
Proven ability to influence decisions through expertise and execution.
Proven ability to support and develop less-experienced teammates.
Experience in life sciences, healthcare, biotechnology, or highly regulated industries (preferred).
Experience with multimodal AI, scientific machine learning, computational biology, or cheminformatics (preferred).
Experience implementing responsible AI practices, evaluation frameworks, and governance controls (preferred).
Evidence of technical impact through deployed systems, publications, patents, open-source contributions, or reusable engineering platforms (preferred).
Permanent work authorization in the United States required.
Candidates must be authorized to be employed in the U.S. by any employer.

Skills

Large Language Models (LLMs)
Agentic AI Systems
Multimodal Learning
Scientific Machine Learning
Retrieval-Augmented Generation (RAG)
Knowledge Graphs
Distributed Training and Inference
AI Platforms and MLOps
AI Evaluation and Benchmarking
Python
PyTorch
JAX
Software Architecture
System Design
APIs
Testing
Debugging
Version Control
Technical Documentation
Containers
Orchestration
CI/CD
Deployment Workflows
Cloud Computing
Distributed Computing
HPC
Multimodal AI
Scientific Machine Learning
Computational Biology
Cheminformatics
Responsible AI
AI Evaluation Frameworks
Governance Controls

Location

Hybrid

Work Type

Hybrid
Full-time

Experience Level

Senior
2+ years relevant experience (Master's)
4+ years relevant experience (Bachelor's)

Education Level

PhD in Computer Science, Computer Engineering, Electrical Engineering, Applied Mathematics, or a related technical discipline
Master's degree
Bachelor's degree

Salary/Compensations

$106,000.00 - $176,600.00

Benefits

Participation in Pfizer’s Global Performance Plan with a bonus target of 15.0% of the base salary.
Eligibility to participate in our share-based long-term incentive program.
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.
Health benefits including medical, prescription drug, dental, and vision coverage.
Relocation assistance may be available.

About the Company

At Pfizer, we're investing in the future of AI-enabled drug discovery.
AI is becoming a foundational capability across Pfizer's R&D organization.
We are building an environment where exceptional engineers can tackle technically ambitious challenges, work with world-class scientific experts, and contribute to innovations that have the potential to improve lives around the world.

Equal Opportunity

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.