AI Engineer

About usWe're reverse-engineering the origin of life - one of the great unsolved problems in science, and one we think AI finally makes tractable. We believe that understanding this transition, from geochemistry to biochemistry, will let us orchestrate molecular networks and build systems that are more capable, adaptive, efficient, and intelligent.If we succeed, the applications are vast: from catalysis and green synthesis to ab initio synthetic biology and programmable matter. Understanding and harnessing these processes could let ten billion of us thrive on this planet - and let us dream that diverse life keeps evolving and thriving beyond it.We're a small, diverse team of AI engineers, computational scientists, and bench scientists.

We hold ourselves to the rigor of a research institute, but we ship like an engineering firm. Global team, HQs in Cambridge, MA and London, UK.The roleYou'll design and train frontier models across biology and chemistry - molecular structure and dynamics, reactions, whole reaction networks. What your models predict decides what the wet labs run next; what the labs find decides your next model.

We'll back an approach that might not work if the upside is large enough.What you'll doTrain large models across three threads: enzyme - substrate prediction, neural network potentials, and inverse design of reaction networksOwn models end to end - architecture, data pipelines, training, debugging, evaluationWork directly with chemists and biochemists, and translate between the two fields fluentlyFold experimental feedback from partner labs into each iterationEssential experienceDemonstrated experience training large models end to end, with the depth to discuss in detail what broke and how you fixed itStrong ML engineering fundamentals: architectures, training dynamics, data pipelines, and evaluationAbility to communicate complex technical concepts clearly to colleagues whose first language is biology and chemistry rather than AIHighly preferredPhD 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 workflowsLogisticsCompensation is highly competitive. We're also able to sponsor visas for the right candidate.Find Jobs in United Kingdom on Arbeitnow