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ML Engineer - Large Molecules

middleremoteRemote (UTC +/- 2 hrs)3d ago
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📊 AI / ML / Data Science: salaries and demand on the market
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fine-tuningkubernetesmlopspythonpytorch
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Description
About Apheris At Apheris, we are building the future of how AI is applied in pharmaceutical R&D. We enable leading pharmaceutical teams to discover and develop drugs faster. We host the industry’s largest federated data networks for drug discovery AI, spanning co-folding, ADMET, and antibody developability. Across these networks, models are trained on proprietary industry datasets to achieve higher performance and broader applicability while keeping data control and IP protected. We deliver these superior models through drug discovery applications that enable teams to run them at scale, further customize them, and integrate them into existing R&D workflows. AI Structural Biology (AISB) Network: Pharmaceutical companies collaborate in the field of co-folding, structure-based binding affinity predictions and antibody design. ADMET Network: Pharmaceutical and biotech companies collaborate to improve small-molecule property prediction and expand to further drug modalities. Antibody Developability Network: Pharma partners collaborate to federate historical and purpose-built antibody developability datasets for secure ML training, without data leaving each partner’s environment. About the role We are looking for an ML Engineer to join our large molecule ML team and build the models behind our antibody, co-folding and developability programs. This is a hands-on role at the intersection of foundation models, structural biology, protein engineering and federated learning. You will bui
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