Responsibilities

This unique role is for a scientist who is passionate about being a catalyst for applying cutting-edge AI to solve real-world drug discovery challenges. You will be the critical bridge between our long-term research and our experimental drug discovery programs. Your mission is to build, evaluate, monitor, and improve our state-of-the-art models directly into active drug programs, leading the charge on model validation, deployment, and analysis to guide the discovery of new medicines.
Positions are available at various levels of seniority: Senior, Staff, and Principal.
Work directly with project teams to assess model performance and utility, including applicability to current project needs, and collaborate with ML and engineering teams to resolve issues or add new functionality.
Assist experimental colleagues with use and interpretation of model predictions by providing context about model quality and prediction uncertainty.
Evaluate model quality by validating predictions against project data and internal or external benchmarks.
Curate internal and external datasets for model training and validation (in collaboration with experimental teams).
Contribute to design and analysis of experiments on model changes and alternative architectures.
A seasoned computational scientist with a proven track record of machine learning based methods to impact small molecule drug discovery projects.
A cheminformatics expert, fluent in the language of molecular data with hands-on mastery of tools like RDKit or OpenEye.
A scientist who speaks the language of experimental drug discovery, with a strong familiarity with common assay types (biochemical/binding/cell-based assays, in vivo studies, etc.) and CADD workflows (docking, virtual screening, ADME prediction, etc.).
A rigorous data scientist, with experience inmodeling and analysis of small molecule datasets and passion for statistical validation, uncertainty quantification, and deriving clear insights from complex, noisy data.
A hands-on applied scientist and software engineer with strong coding skills in Python and a deep practical knowledge of the applied ML toolkit (e.g., scikit-learn, PyTorch).

Applied ML Scientist (Staff / Principal) at Genesis Molecular AI · LumiJobs

Applied ML Scientist (Staff / Principal)

Responsibilities

Qualification

Preferred

Benefits

Company

Genesis Molecular AI

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