Act as a trusted technical partner to DMPK scientists, clinical pharmacologists, statisticians, clinicians, and research leaders
Facilitate cross-functional alignment, and translate scientific and operational needs into clear AI/ML solution requirements
Design, develop, benchmark and deploy AI agents to support PDMB and clinical workflows
Develop and apply machine learning and deep learning models for DMPK and clinical applications
Define benchmarks and success metrics for AI agents and ML models
Design and track value metrics such as time savings, cost avoidance, throughput improvements, and decision quality

Master’s (with 3 years) or Ph.D. in Data Science, Computer Science, Computational Chemistry, Bioinformatics, Applied Mathematics or a related quantitative field
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) required
Proven experience integrating and modeling multimodal datasets (omics, chemical, textual, imaging)
Experience in model evaluation and benchmarking
Strong software development skills in Python and 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

medical, dental, vision healthcare and other insurance benefits (for employee and family)
retirement benefits, including 401(k)
paid holidays, vacation, and compassionate and sick days

Senior Scientist, Agentic AI, Machine Learning

Key skills