Machine Learning Engineer

BEPC is actively looking for a Machine Learning Engineer in South San Francisco, CA area! W2 Contract – 12 months with possible extensions! Benefits include medical, dental, vision, and life insurance Pay Rate: $79.81 - $82.81/hour - Determined based on experience Onsite role Note: This is a W2 only role — C2C, C2H, and W2 referrals will not be considered We are looking for talented Machine Learning Engineers to join Prescient Design, a division devoted to developing structural and machine learning based methods for molecular design within Research and Early Development (gRED) organization. The successful candidate will manage projects deploying new techniques for machine learning based molecular optimization for the analysis and design of small and large molecule drugs within target-driven design campaigns. Special focus will be given to engineering pipelines for probabilistic molecular property prediction and Bayesian acquisition for active learning-based drug discovery. Additional activities may extend to include engineering pipelines for molecular generative modeling. Summary of Duties and Responsibilities: • You will join Prescient Design within the Computational Sciences organization in • gRED. Your peers will be machine learning scientists, engineers, computational chemists, and computational biologists. • You will closely collaborate with scientists within Prescient and across gRED. • You will develop machine learning and Bayesian optimization workflows to analyze existing, and design new, small and large molecules. • You will be expected to form close working relationships with small molecule and protein therapeutic development efforts across the gRED organization. • You will be expected to work on existing projects and generate new project ideas. Qualifications: • PhD degree in a quantitative field ( e.g. , Computer Science, Chemistry, Chemical Engineering, Computational Biology, Physics), or MS degree and 3+ years of industry experience. • Demonstrated experience with machine learning libraries in production-ready workflows (e.g., PyTorch + Lightning + Weights and Biases) • Record of achievement, including at least one high-impact first author publication or equivalent. • Excellent written, visual, and oral communication and collaboration skills. Preferred Qualifications or Familiarity: • Experience with physical modeling methods (e.g., molecular dynamics) and cheminformatics toolkits (e.g., rdkit) • Previous focus on one or more of these areas: molecular property prediction, computational chemistry, de novo drug design, medicinal chemistry, small molecule design, self-supervised learning, geometric deep learning, Bayesian optimization, probabilistic modeling, statistical methods. • Public portfolio of computational projects (available on e.g. GitHub). Technical expertise in at least two of the following areas: cell-based functional assays, image acquisition/analysis, molecular assays (NGS, RT-PCR, dd-PCR), flow cytometry. • Proven ability to multitask, collaborate, and communicate effectively, including leading training sessions. About BEPC BEPC Inc., founded in 2007, is a 100% employee-owned company providing top-tier consulting and staffing solutions across industries like technology, engineering, manufacturing, and project management. At BEPC, we are driven by innovation and a commitment to excellence. We take pride in fostering a collaborative and innovative environment where our team members thrive. With competitive benefits, including medical, dental, vision, and life insurance, BEPC is dedicated to supporting our employees' personal and professional growth. Apply Now! Qualified candidates are encouraged to apply by submitting an up-to-date resume that highlights how your experience aligns with the role. Please include specific examples that demonstrate your qualifications. We look forward to connecting with you!