Senior Director / Vice President, Machine Learning (Generative Chemistry)
Core
Lead AI/ML and cheminformatics projects to build next-gen multi-modal generative models for biomolecular design and drug discovery.
Role type
Senior Director/VP Machine Learning (Generative Chemistry)
Builds
Multi-modal generative models, drug design systems, molecular modeling pipelines, and LLM/agentic workflows for biomolecular design.
Domain
Biotechnology / Generative Chemistry / AI for Drug Discovery
Deliverable
production ML models
Required skills
Generative modeling (diffusion/flow/VAEs), Deep learning architectures, Python, MLOps (data contracts, experiment tracking, CI/CD), Cloud infrastructure (AWS), Workflow orchestration, Cheminformatics tools (RDKit, Rosetta, OpenMM), LLM/agentic automation
Preferred skills
Protein modeling/design, Docking rescoring, Biophysics/MD, MLOps expertise (DVC, MLflow, Terraform), Vector search, Internal tooling (FastAPI, Streamlit)
Technologies
PyTorch, JAX, TensorFlow, Docker, Terraform, AWS (S3, Batch, ECS, EKS, SageMaker), Airflow, Prefect, Argo, Redshift, Snowflake, FAISS, pgvector, FastAPI, Streamlit, Gradio, RDKit, Rosetta, Prody, Biopython, PyMOL, OpenMM, Dagster
Responsibilities
Lead development and reporting of AI/ML projects aligned with strategic plans; oversee method and pipeline development; promote operational excellence; manage and mentor cross-functional teams; contribute to project planning and risk management; scout emerging literature to propose new development strategies.
Seniority
Senior Director/VP, hands-on IC with leadership responsibilities
