Applied ML Scientist Staff Principal
AI-focused biotechnology company developing molecular-AI systems and small-molecule drug candidates for internal programs and pharmaceutical partners.
Funding history
About Genesis Molecular AI
Genesis Molecular AI combines foundation models, generative and predictive AI, and physics-based computation in its GEMS platform for small- and medium-size-molecule drug discovery.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will bridge machine learning research and experimental drug discovery by evaluating, validating, deploying, and improving models used in active programs. You will curate datasets, analyze model predictions and uncertainty, support experimental colleagues, and help design experiments for model changes and alternative architectures.
Requirements
- Machine learning experience affecting small-molecule drug discovery projects
- Cheminformatics expertise
- Experience with experimental drug discovery assays and CADD workflows
- Small-molecule dataset modeling and analysis
- Statistical validation and uncertainty quantification
- Python
- scikit-learn
- PyTorch
- Communication
Responsibilities
- Assess model performance and utility for project needs
- Collaborate with ML and engineering teams to resolve model issues and add functionality
- Help experimental colleagues use and interpret model predictions
- Validate predictions against project data and benchmarks
- Curate datasets for model training and validation
- Design and analyze experiments for model changes and alternative architectures
Benefits
- Equity
- Medical insurance
- Dental insurance
- Vision insurance
- 401(k) plan
- Unlimited PTO
- Free office lunches and dinners
- Paid family leave
- Life insurance
- Long-term disability insurance
- Short-term disability insurance