Dayhoff Labs - AI Engineer

Cambridge, MA, London, UK1mo ago

Requirements

• Demonstrated experience training large models end to end, with the depth to discuss in detail what broke and how you fixed it • Strong ML engineering fundamentals: architectures, training dynamics, data pipelines, and evaluation • Ability to communicate complex technical concepts clearly to colleagues whose first language is biology and chemistry rather than AI • Highly preferred • Highly preferred • PhD in a quantitative field (common on our team, but depth matters more than credentials) • Experience in ML-for-chemistry or ML-for-biology (e.g., neural network potentials, graph neural networks, protein or reaction models) • Familiarity with computational chemistry or biochemistry concepts and workflows • Logistics • Compensation is highly competitive. We're also able to sponsor visas for the right candidate.

Responsibilities

• Train large models across three threads: enzyme–substrate prediction, neural network potentials, and inverse design of reaction networks • Own models end to end — architecture, data pipelines, training, debugging, evaluation • Work directly with chemists and biochemists, and translate between the two fields fluently • Fold experimental feedback from partner labs into each iteration