DigiChem is reshaping how new chemicals are developed and brought to market by developing the most powerful system for synthesizing molecules ever made, leveraging AI and deep integration with physical hardware to perform chemistry on demand and easily scale to manufacturing.
Requirements
- Professional experience building and deploying ML systems in production.
- Deep Python expertise for ML + backend and proficiency with PyTorch, TensorFlow, or similar tools.
- Strong cheminformatics foundation with tools such as RDKit for standardization, descriptors/ECFP, reaction handling, SA scores, enumeration.
- Practical knowledge of reaction datasets, atom-mapping, and template extraction; understanding of stereochemistry/tautomerism/charge states.
- MLOps fundamentals: Docker, Kubernetes, FastAPI/gRPC, experiment tracking (MLflow or Weights & Biases), data/version control (DVC/Git-LFS), CI/CD.
- Data engineering fluency: SQL, data modeling, and pipeline tooling
- Evidence of rigorous evaluation practices and writing design docs.
Responsibilities
- Define the end-to-end technical architecture for cheminformatics services
- Translate synthesis planning requirements into technical specs in partnership with our chemists
- Design the data pipeline for molecules, reactions, and procedures
- Build and benchmark models that enable our on-demand chemistry platform
- Package models into production-ready services
- Evaluate and select from open source and commercial tools
Other
- partnering closely with synthetic chemists and platform engineers.
- We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
- Even if you don't check every box, but see yourself contributing, please apply.
