{"id":3340820,"url":"https://alion.io/job/dayhoff-labs-experimental-systems-engineer-analytical-chemistry","title":"Experimental Systems Engineer, Analytical Chemistry","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":"Biotech","role_family":"Biotech","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","Houston, United States"],"countries":["US","GB"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":111000,"max_usd":255000,"period":"year","method":"role_country_seniority_unknown","sample_n":1243},"experience_years_min":null,"visa_sponsorship":true,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Chromatography","optional":false},{"name":"HPLC","optional":false},{"name":"Mass Spectrometry","optional":false},{"name":"Python","optional":false}],"status":"live","first_seen_at":"2026-07-06T10:28:17Z","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 build new ways of watching chemistry happen - liquid-phase reaction networks, enzymatic and not, evolving in real time. This role suits people who build things and figure things out: prototype a measurement setup, learn fast whether it tells you anything trustworthy, keep it or bin it.\nWhat you'll do\nDesign and build prototype systems for monitoring aqueous chemical reaction networks in real time\n\nWork with small CSTRs, flow reactors, microfluidic devices, pumps, valves, tubing, flow cells, and autosamplers\n\nEvaluate analytical technologies including Raman, UV-Vis, fluorescence, IR, NMR, LC-MS, HPLC, electrochemical sensing, and low-cost process probes\n\nBuild Python-based tools for data acquisition, instrument control, signal processing, and visualisation\n\nCombine continuous measurements with sampled analytical data to reconstruct the time evolution of chemical mixtures\n\nWork closely with chemists, enzymologists, computational scientists, and ML engineers to turn messy signals into useful data\n\nEssential experience\nYou'll have some but not necessarily all of the following:\nBuilding experimental hardware or analytical setups with your own hands\n\nComfort with liquid handling systems: pumps, valves, tubing, flow cells, leaks, bubbles, fouling, and drift\n\nAt least some analytical chemistry methods (spectroscopy, chromatography, mass spectrometry, NMR, or electrochemical sensing)\n\nPractical Python for data acquisition, analysis, plotting, and automation\n\nWillingness to move between the wet lab, instrument manuals, notebooks, code, and physical prototyping\n\nGood judgement about when a measurement is meaningful, when it is misleading, and when the setup needs rebuilding\n\nHighly preferred\nAny of Raman, FTIR, UV-Vis, fluorescence, online NMR, LC-MS, HPLC, or MS workflows\n\nLab automation: Arduino, Raspberry Pi, LabJack, NI DAQ, serial instrument control, autosamplers, or custom data logging\n\nBuilding fast prototypes in a startup, academic lab, instrument company, or hardware-heavy research environment\n\nLogistics\nCompensation is highly competitive. 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