We’re defining a category on problems pharma can’t solve alone.
AI in drug discovery is now constrained by data access. High-quality proprietary data is distributed across pharmaceutical companies, leaving no single organization with enough coverage to train generalizable models. Federated networks are becoming necessary infrastructure to access industrial drug discovery data for AI model training.
What you’ll build
ML research & science
Federated training of structural biology, ADMET, and Antibody Developability foundation models. Fine-tuning on proprietary pharma data. Privacy attacks and defenses on molecular models. Federated benchmarking design.
Engineering
Build the product that pharma’s most demanding IT and legal teams will deploy inside their environments. Apheris Gateway, the Hub, ApherisFold, and the connectors and infrastructure that make federated training work across AWS, on-prem, and airgapped sites. Cloud platform, infra, applied ML engineering, and agentic AI engineering.
Drug discovery applications
Translate federated models into products R&D teams use daily across co-folding, structure-based design, ADMET prediction, and antibody developability. Customer-facing solutions engineering, AI program management, and scientific advisory roles.
Commercial & operations
Align network members, scientific plans, advisory boards, and multi-party governance across top pharma organizations while driving partner success and operational excellence across people, finance, and talent acquisition.
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What our team says about working at Apheris
This is the best time to be at Apheris. We’re building the largest federated data networks in pharma, the model results are very impressive, and the work in front of us is to leverage this data moat and make sure our partners can use the superior models in production across their drug programs. We have incredible talent at Apheris and a commitment to continuously grow talent density. Apheris is a place for people that want to have macro-level impact. We build the data foundation that will lead to the next set of AlphaFold-level breakthroughs.