Our client is a disruptive drug discovery company who are revolutionizing the Biotech industry. They are hiring Principal or Staff Level Machine Learning Engineer to join the team in San Francisco. The successful candidate will be responsible for implementing and scaling state-of-the-art molecular machine learning models. Responsibilities Implement Machine Learning Models and Software components to accelerate molecular property prediction and chemical space exploration. Build training pipelines for large scale chemical models. Create scalable pipelines for chemical data processing and dataset creation. Establish best practices for molecular ML development. Skillset Masters or PhD degree in Computer Science, Computational Chemistry or similar. At least five years of hands-on experience implementing complex molecular ML Systems. Strong understanding of technical molecular ML Architectures and techniques. Expert knowledge of PyTorch best practices. Expertise in multi-model Machine Learning, large scale model training and/or quantum chemistry libraries is a plus. Experience in datasets and feature engineering for pharmatech, including PubChem, molecule libraries, genomics, proteomics or clinical trial biomarkers is a plus. Experience with computational chemistry packages: ex RDKit, OpenMM, ParMe, GROMACS, Ambertools, MDAnalysis is a bonus. Previous experience in a startup environment is desirable. Benefits Salary: $200-250k + equity Health, dental and vision insurance. Hybrid work environment – 3 days onsite in South San Francisco Interested? Apply Today!! 49416

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