Machine Learning Scientist/Senior Machine Learning Scientist - Agents for Applied Small Molecule Drug Design, AI for Drug Discovery
Core
Designing and building autonomous, LLM-driven agentic workflows that orchestrate ML models, physics-based methods, and cheminformatics tools to accelerate small-molecule drug design.
Role type
Senior IC Machine Learning Scientist (Agentic Workflows for Drug Discovery)
Builds
Autonomous agentic workflows integrating ML models, physics-based methods, and cheminformatics tools for drug discovery
Domain
Pharmaceutical industry, AI for Drug Discovery, Small-molecule design
Deliverable
production ML models
Required skills
LLM-driven agent development, tool orchestration, linear algebra, probability, optimization, Graph Neural Networks (GNNs), sequence/language models, reinforcement learning, Python, LangChain, PyTorch/JAX, cheminformatics toolkits (RDKit/OpenEye)
Preferred skills
Multi-tool/multi-agent scientific pipeline orchestration, small molecule drug discovery value chain experience, structural biology datasets familiarity
Technologies
LangChain, PyTorch, JAX, RDKit, OpenEye
Responsibilities
Design and apply agentic workflows and ML models for small-molecule drug design challenges; Fine-tune foundation models for drug discovery using internal/external datasets; Optimize agent-derived hypotheses with computational and medicinal chemists; Drive scientific impact via publications, open-source releases, and conference talks; Collaborate with computational/experimental researchers and academic partners
Seniority
Senior, hands-on IC