Principal Scientist, Machine Learning - Biomolecules
Core
Lead multiple AI/ML or computational projects across early-stage ventures to define pragmatic AI strategies, oversee method and platform development, and ensure rigor in model development and scaling.
Role type
Principal Scientist (Embedded ML/Computational)
Builds
AI-first companies in human health, sustainability, and beyond
Domain
Biotechnology, AI/ML, Drug Design, Molecular Modeling
Deliverable
production ML models
Required skills
Python, modern ML frameworks (PyTorch, JAX, TensorFlow), deep learning architectures, version control, databases, informatics software
Preferred skills
MLOps (DVC, LakeFS, MLflow, AWS, Docker, Terraform, CI/CD), generative modeling (diffusion, flow, VAEs), docking rescoring, workflow orchestration (Airflow, Prefect, Argo), vector search, lightweight internal tools
Technologies
PyTorch, JAX, TensorFlow, Python, AWS, Docker, Terraform, CDK, GitHub Actions, DVC, LakeFS, MLflow, SageMaker, Redshift, Snowflake, FAISS, pgvector, FastAPI, Streamlit, Gradio, Airflow, Prefect, Argo, gnina, DiffDock
Responsibilities
Lead development, implementation, control, and reporting of several AI/ML or computational projects within assigned ventures; Take a specialized technical role to oversee method development, pipeline development, and LLM-based agent/workflow design; Promote operational excellence in AI projects by educating cross-functional collaborators; Manage and/or coordinate internal and external scientists/engineers and cross-functional project teams; Contribute to project planning, including budgets, resources, and timelines; Independently scout emerging literature and the AI/ML landscape to propose new development strategies
Seniority
Principal, strategy & mentorship
