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About the Role

Develop, benchmark, deploy, and integrate world-class agentic AI and Machine Learning within the Pharmacokinetics, Dynamics, Metabolism, and Bioanalytics (PDMB) department. Partner with scientists to pioneer AI/ML innovations that augment scientific insight, streamline workflows, and improve decision-making across the drug development lifecycle to advance transformative medicines. This role requires a strong technical background, collaboration with stakeholders, and the ability to communicate across science, technology, and business strategy to deliver "human in the loop" AI/ML. It is central to integrating AI/ML for insight and efficiency across the R&D portfolio to deliver transformative medicines for patients.

Responsibilities

Act as a trusted technical partner to DMPK scientists, clinical pharmacologists, statisticians, clinicians, and research leaders.
Facilitate cross-functional alignment.
Translate scientific and operational needs into clear AI/ML solution requirements.
Communicate clearly with technical and non‑technical audiences, explaining capabilities, limitations, and trade-offs.
Design, develop, benchmark, and deploy AI agents to support PDMB and clinical workflows.
Support automated report generation, quality evaluation, consistency checks, process monitoring, deviation detection, scheduling, prioritization, and alerting systems.
Apply agent development frameworks and architectures (e.g., tool-using agents, workflow agents, human-in-the-loop systems).
Integrate agents and ML methods into existing R&D platforms, laboratory systems, data lakes, and clinical data environments.
Develop and apply machine learning and deep learning models for DMPK and clinical applications.
Build and evaluate simulation and hybrid ML–mechanistic models to support decision-making in discovery and development.
Apply best practices in model validation, benchmarking, uncertainty estimation, and performance monitoring.
Define benchmarks and success metrics for AI agents and ML models, including scientific quality, operational efficiency, and user adoption.
Implement ongoing monitoring for model drift, data quality, agent behavior, and downstream impact.
Contribute to responsible AI practices, including transparency, reproducibility, governance, and compliance with GxP considerations.
Define and track value metrics such as time savings, cost avoidance, throughput improvements, and decision quality.
Quantify and communicate return on investment (ROI) and business impact from deployed AI and ML solutions.
Support prioritization of AI initiatives based on scientific impact, feasibility, and value creation.

Requirements

Master’s degree (with 3 years of experience) or Ph.D. in Data Science, Computer Science, Computational Chemistry, Bioinformatics, Applied Mathematics, or a related quantitative field.
Relevant experience developing and deploying AI, machine learning, or Analytics systems in industry or applied research environments.
Hands-on experience with large language models and agentic AI frameworks (fine-tuning, prompt engineering, multi-agent orchestration, tool use, and API-based production orchestration).
Proven experience integrating and modeling multimodal datasets (omics, chemical, textual, imaging).
Experience in model evaluation and benchmarking.
Strong software development skills in Python.
Familiarity with modern ML frameworks (e.g., PyTorch, TensorFlow), MLOps tools, cloud platforms (AWS preferred), and HPC environments.
Experience driving consensus in cross-functional teams spanning science, engineering, and operations.
Experience in stakeholder management and influencing without authority.
Excellent communication skills; ability to translate complex technical work to domain experts and leadership.

Skills

Strong foundation in machine learning algorithms, including deep learning, supervised/unsupervised learning, and time-series or sequence modeling.
Experience with foundation models (e.g., large language models, multimodal models) and techniques for adaptation (prompting, fine-tuning, retrieval-augmented generation).
Practical experience with AI agent frameworks, orchestration, and tool integration.
Expertise in model evaluation and benchmarking, including offline metrics and real-world performance monitoring.
Proven ability to work with large-scale, heterogeneous datasets (biological, chemical, clinical, operational).
Proficiency in Python and modern ML/data science tooling.
Experience with scalable data and model deployment environments.
Demonstrated strength in stakeholder management and influencing without authority.
Experience driving consensus in cross-functional teams spanning science, engineering, and operations.
Ability to independently lead initiatives from problem definition through deployment and impact measurement.
Strong written and verbal communication skills.
Agentic AI
Agentic Design
Data Modeling
Data Science
Data Visualization
Machine Learning (ML)
Machine Learning Methods
Machine Learning Model Development
Python (Programming Language)
Report Generation Software
Stakeholder Relationship Management
Prior experience working in pharmaceutical or biotechnology R&D environments (Preferred).
Familiarity with PK/PD modeling, DMPK assays, and clinical pharmacology concepts (Preferred).
Exposure to GxP-regulated environments and validation considerations for AI/ML systems (Preferred).
Experience deploying AI systems with human-in-the-loop workflows (Preferred).

Location

South San Francisco, CA
Boston, MA
West Point, PA

Work Type

Full-time
Hybrid

Experience Level

Senior level
3+ years of relevant experience (with Master's degree)

Education Level

Master’s degree in Data Science, Computer Science, Computational Chemistry, Bioinformatics, Applied Mathematics or a related quantitative field.
Ph.D. in Data Science, Computer Science, Computational Chemistry, Bioinformatics, Applied Mathematics or a related quantitative field.

Salary/Compensations

$129,000.00 - $203,100.00

Benefits

Annual bonus
Long-term incentive
Medical healthcare benefits
Dental healthcare benefits
Vision healthcare benefits
Other insurance benefits (for employee and family)
Retirement benefits, including 401(k)
Paid holidays
Vacation days
Compassionate days
Sick days

About the Company

Global health care leader with a diversified portfolio of prescription medicines, vaccines, and animal health products.
Legacy of innovation and inventiveness for over a century.
Success backed by ethical integrity, forward momentum, and a mission to achieve new milestones in global healthcare.

Equal Opportunity

Committed to inclusion and ensuring candidates can engage in a hiring process that exhibits their true capabilities.
Provides equal opportunities to all employees and applicants for employment.
Prohibits discrimination on the basis of race, color, age, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability status, or other applicable legally protected characteristics.
Complies with all affirmative action requirements for protected veterans and individuals with disabilities as a federal contractor.
Embraces the value of bringing together talented, committed people with diverse experiences, perspectives, skills, and backgrounds in an inclusive environment.
Encourages colleagues to respectfully challenge one another’s thinking and approach problems collectively.
For San Francisco Residents: Considers qualified applicants with arrest and conviction records for employment in compliance with the San Francisco Fair Chance Ordinance.
For Los Angeles Residents: Considers for employment all qualified applicants, including those with criminal histories, consistent with applicable state and local laws, including the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance.