{"id":3264269,"url":"https://alion.io/job/latchbio-ai-biologist-peptide-discovery","title":"Ai Biologist - Peptide Discovery","company":{"id":171847,"name":"LatchBio","domain":"latch.bio","url":"https://alion.io/company/latchbio","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":"Science & Research","role_family":"Science & Research","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"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":120000,"max":180000,"currency":"USD","period":"year","gross":null,"usd_annual":180000},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":true,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Claude","optional":false},{"name":"Cursor","optional":false},{"name":"Python","optional":false}],"status":"live","first_seen_at":"2026-10-26T07:13:05Z","employer_posted_date":"2026-10-26","last_verified_at":"2026-10-31T11:08:10Z","board_verified":true,"closed_at":null,"days_open":5,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":5},"description":"AI Biologist - Peptide Discovery\nLatch builds rigorous scientific benchmarks (benchmarks.bio) for AI agents across biology. We work with frontier labs and pharma to measure whether agents can handle real biological workflows: the messy, multi-layer reasoning that matters in the field.\nWe’re seeking an AI Biologist to join our Peptide Discovery team, pushing what AI can achieve in therapeutic peptide discovery.\nAbout the Role. You will be the scientific authority on ground truth, testing whether agents can reason like an expert peptide discovery scientist. AI agents today struggle to interpret raw selection, biophysical, and structural data, to separate true hits from artifacts, and to make the calls that move a peptide from target to candidate. The data often misleads: enrichment can be a propagation artifact, protection is not contact, and binding is not function. Knowing what the evidence actually supports is the work. You will work with software engineers and scientists to build the tasks and datasets behind our benchmarks. They span linear, macrocyclic, and constrained peptides against protein targets, including protein-protein interactions, from target tractability to candidate nomination. Your judgment will set the standard agent outputs are held to, including:\nBuild the task\nDefine what expert reasoning looks like for a peptide discovery question, and write gold-standard answers with the rationale an experienced peptide scientist would defend\n\nDesign realistic scenarios across the discovery arc: target tractability, hit generation, hit confirmation and kinetics, binding-site mapping, functional confirmation, and lead optimization\n\nCurate datasets from real programs: display-selection read counts, SPR/BLI sensorgrams, fluorescence-polarization titrations, affinity-selection MS, HDX-MS, crosslinking-MS, NMR chemical-shift perturbation, dose-response, and permeability and stability data\n\nBuild analysis pipelines in Python, from enrichment analysis to kinetic and dose-response fitting, that produce verifiable ground truth with tolerances that hold across replicates and fitting routines\n\nPartner with software engineers to turn your judgment into new workflows\n\nSet the hard calls\nTest whether agents distinguish true signal from artifact, such as propagation or expression artifacts enriched across rounds, sensorgrams distorted by aggregation or superstoichiometric binding, or HDX protection mistaken for direct contact\n\nAdjudicate conflicting evidence: reconcile orthogonal binding-site datasets, decide between competitive and allosteric engagement, and identify which experiment would settle the call\n\nTest whether agents weigh the right tradeoffs: binding versus function, potency versus developability, and when added constraint or affinity costs a property that matters more\n\nJudge the agent\nInterrogate agent reasoning step by step, and challenge conclusions that sound right but would not survive a project review or lab meeting\n\nPinpoint where agents go wrong: why a step fails, what an expert would do instead, and what evidence would change the call\n\nScore agent confidence, rewarding explicit uncertainty over overconfident calls on ambiguous data\n\nRequirements\nPhD in peptide chemistry, biochemistry, biophysics, structural biology, medicinal chemistry, or a related field\n\nSenior, hands-on peptide discovery experience: you have personally analyzed real program data, not just supervised it\n\nDirect experience with at least one of: display selection (phage, mRNA, ribosome, RaPID, or DNA-encoded libraries), SPR/BLI or FP binding kinetics, binding-site mapping by structural MS or NMR, or peptide developability (PAMPA/Caco-2 permeability, proteolytic and serum stability)\n\nDeep expertise in at least one area (display and selection, biophysics, structural mapping, or peptide medicinal chemistry) and working fluency across the others\n\nStrong command of experimental design, quantitative data analysis in Python or R, and statistics\n\nAI-ready from day one: daily use of Claude, Cursor, or similar agents, with the judgment to spot where model reasoning is technically correct but scientifically unsound\n\nConfidence to overrule an AI agent when the evidence demands it, and the openness to update when shown wrong\n\nAbility to calibrate confidence and communicate uncertainty rather than defaulting to binary calls\n\nBonus: peptide format and chemistry experience, such as macrocyclization, hydrocarbon stapling, N-methylation, D- and non-canonical residues, or HELM encoding\n\nBonus: target tractability or de novo design experience, such as PPI hotspot analysis, human-genetic evidence for therapeutic direction, or computational design with Rosetta or RFdiffusion\n\nCulture. We practice radical transparency: you’ll know how the company is doing, what’s working, and what isn’t. It’ll always be us against the problem, never each other. We’re opinionated but respectful, and we bring solutions with our problems. You decide how you work; we judge the output. We use AI constantly, so what we reward is original expert judgment, not AI output passed off as your own. You’ll start on the bench that fits your expertise and can move across teams as you build a track record. People who do well here and bring leadership experience can move quickly into senior roles. Outside of work, we have company outings most months, team off-sites, a Latch run club, cycling, boxing, ice skating, and soccer. Feel free to add to the list.\nCompensation & Logistics\nContract: 1099 (or W-8BEN internationally), no end date\n\nPay: guaranteed for weeks 1-4 while you ramp, then paid per certified task. Most people in this position earn $120K-$180K+ (uncapped upside); certify twice the tasks/week, earn twice the pay that week.\n\nCommitment: full-time, on your own schedule. Most of the team works 40+ hours a week.\n\nMeetings: a few pod check-ins a week. The rest of your time is yours.\n\nLocation: remote (anywhere), hybrid, or onsite in SF. We prefer onsite.\n\nOnsite perks: catered lunch and dinner daily, a waterfront office in Mission Bay, and monthly parking when available\n\nWork authorization: US citizens, permanent residents, and OPT holders. We can’t support STEM OPT extensions or sponsorship.\n\nInterview Process\nWe move fast: about 2-3 weeks from your first call, to offer.\nIntro Screen - Latch Talent Team\n\nTake-Home Project - HackerRank\n\nTechnical Interview - Member of Technical Staff\n\nCulture Interview - C-Suite\n\nOffer","description_format":"text","description_chars":6467,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"phd","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Bioinformatics","Scientific & Lab Software"],"lifecycle":[{"event":"open","at":"2026-10-26T07:58:38Z"}],"visa":[{"country":"US","licensed_sponsor":true,"evidence":"H-1B filings in 12 months: 5","filings_12m":5,"filings_prev_12m":1,"green_card_filings_12m":0,"median_offered_wage_usd":112500,"route":null,"cap_exempt":false,"checked_at":"2026-10-29T16:27:21+00:00","sources":["US Department of Labor: LCA disclosure data (H-1B, H-1B1, E-3)"],"filings_for_role_12m":0}],"liveness":{"score":90,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.899,"p_room":1,"age_days":4,"expected_fill_days":30,"reasons":["conf:2","velocity","win:early"],"computed_at":"2026-10-31T05:58:55Z"},"pay":{"stated_usd_annual":180000,"is_top_pay":true},"html_url":"https://alion.io/job/latchbio-ai-biologist-peptide-discovery","json_url":"https://alion.io/job/latchbio-ai-biologist-peptide-discovery.json","meta":{"generated_at":"2026-10-31T12:26:14Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":19211,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-11-01T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":171847},"rest":"https://alion.io/mcp/rest/get_company?id=171847"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Flatchbio-ai-biologist-peptide-discovery"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Flatchbio-ai-biologist-peptide-discovery"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Flatchbio-ai-biologist-peptide-discovery"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/latchbio-ai-biologist-peptide-discovery\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Flatchbio-ai-biologist-peptide-discovery"}],"agent":{"mcp":"https://alion.io/mcp/jobs","mcp_open":"https://alion.io/mcp/open","next":[{"tool":"get_job","arguments":{"id":3264269}},{"tool":"search_jobs","arguments":{"company":"latch.bio","detail":"compact"}},{"tool":"match_people","arguments":{"job_id":3264269},"note":"people open to offers who fit this vacancy"}],"note":"The same data through MCP tools: https://alion.io/mcp/open needs no sign-in (compact searches, postings, people); https://alion.io/mcp with an Alion account has everything. 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