{"id":3340821,"url":"https://alion.io/job/dayhoff-labs-research-engineer","title":"Research Engineer","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":"2026-10-31T05:58:55Z"}},"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":["San Francisco, United States","London, United Kingdom","Cambridge, United States"],"countries":["US","GB"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":159000,"max_usd":355000,"period":"year","method":"role_country_seniority_unknown","sample_n":4425},"experience_years_min":null,"visa_sponsorship":true,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"AWS","optional":false},{"name":"Function Calling","optional":false},{"name":"GCP","optional":false},{"name":"LLM Evaluation","optional":false},{"name":"Python","optional":false}],"status":"live","first_seen_at":"2026-07-06T10:14:15Z","employer_posted_date":"2026-07-06","last_verified_at":"2026-10-31T10:27:03Z","board_verified":true,"closed_at":null,"days_open":117,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":116},"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 be a generalist research engineer, moving fluidly across our maintenance and research projects wherever leverage is highest. The through-line is using LLMs and agents to build software and complex systems - including for open-ended scientific questions, not just engineering ones. You'll have real latitude to decide what to build and how, and your work will land directly on how fast our researchers move and what our science can do.\nWhat you'll do\nUse LLMs and coding agents to build software and complex systems, and keep advancing the internal agentic systems we use to write our code and maintain our infrastructure\n\nSelf-host and evaluate open-source models, and write the harnesses, tooling, and scaffolding that make agents reliable for our workflows\n\nApply agents to scientific questions - an open-ended remit spanning genuine research, experimentation, and analysis, not only software development\n\nContribute across a variety of maintenance and research projects as priorities shift, from internal tooling to data and model work\n\nKeep our cloud infrastructure and development environments healthy\n\nEssential experience\nDemonstrated ability to use LLMs to write software and build complex systems\n\nHands-on experience with open-source models: self-hosting, evaluation, and writing harnesses or scaffolding around them\n\nStrong Python and the ability to own complex technical systems end to end\n\nComfort working across an unfamiliar codebase and shipping in areas outside your prior expertise\n\nSound engineering fundamentals: version control workflows, testing, and reproducible environments\n\nHighly preferred\nBackground in biology, chemistry, or a related scientific domain\n\nScientific computing or ML/research-tooling experience\n\nSubstantial professional software engineering experience\n\nExperience building or operating agentic systems (multi-step tool use, orchestration, evaluation harnesses)\n\nFamiliarity with cloud infrastructure (AWS or GCP), containerization, and infrastructure-as-code\n\nLogistics\nCompensation is highly competitive. 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