{"id":3340825,"url":"https://alion.io/job/dayhoff-labs-ai-research-scientist","title":"AI Research Scientist","company":{"id":4403902,"name":"Dayhoff Labs","domain":"dayhofflabs.com","url":"https://alion.io/company/dayhoff-labs","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"B","score":75,"open_postings":6,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-11-03T05:54:40Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Cambridge, United States","London, United Kingdom"],"countries":["US","GB"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":132000,"max_usd":293000,"period":"year","method":"role_country_seniority_unknown","sample_n":4425},"experience_years_min":null,"visa_sponsorship":true,"relocation_package":false,"has_equity":false,"technologies":[],"status":"live","first_seen_at":"2026-07-04T17:12:35Z","employer_posted_date":"2026-07-04","last_verified_at":"2026-11-03T16:29:09Z","board_verified":true,"closed_at":null,"days_open":122,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":121},"description":"About us\nWe're reverse-engineering the origin of life - one of the great unsolved problems in science, and one we think AI finally makes tractable. Understanding this transition, from geochemistry to biochemistry, is what will let us orchestrate molecular networks and build systems that are more capable, adaptive, and efficient.\nIf we succeed, the applications are vast: catalysis, green synthesis, ab initio synthetic biology, programmable matter. Understanding and harnessing these processes could let ten billion of us thrive on this planet - and let life keep evolving beyond it.\nWe'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.\nThe role\nYou'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.\nWhat you'll do\nTrain large models across three threads: enzyme-substrate prediction, neural network potentials, and inverse design of reaction networks\n\nOwn models end to end - architecture, data pipelines, training, debugging, evaluation\n\nWork directly with chemists and biochemists, and translate between the two fields fluently\n\nFold new data into each iteration\n\nEssential experience\nDemonstrated experience training large models end to end, with the depth to discuss in detail what broke and how you fixed it\n\nStrong ML engineering fundamentals: architectures, training dynamics, data pipelines, and evaluation\n\nPrior experience working directly on a chemistry, biology, or related physical-science problem, combined with the ability to communicate complex technical concepts clearly to colleagues whose first language is biology or chemistry rather than AI\n\nHighly preferred\nPhD in a quantitative field (common on our team, but depth matters more than credentials)\n\nExperience in ML-for-chemistry or ML-for-biology (e.g., neural network potentials, graph neural networks, protein or reaction models)\n\nLogistics\nCompensation is highly competitive. 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