Ai Biologist - Peptide Discovery

AI Biologist - Peptide Discovery

Latch builds rigorous scientific benchmarks (benchmarks.bio http://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.

We’re seeking an AI Biologist to join our Peptide Discovery team, pushing what AI can achieve in therapeutic peptide discovery.

About 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:

Build the task

- Define what expert reasoning looks like for a peptide discovery question, and write gold-standard answers with the rationale an experienced peptide scientist would defend

- Design realistic scenarios across the discovery arc: target tractability, hit generation, hit confirmation and kinetics, binding-site mapping, functional confirmation, and lead optimization

- Curate 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

- Build 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

- Partner with software engineers to turn your judgment into new workflows

Set the hard calls

- Test 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

- Adjudicate conflicting evidence: reconcile orthogonal binding-site datasets, decide between competitive and allosteric engagement, and identify which experiment would settle the call

- Test whether agents weigh the right tradeoffs: binding versus function, potency versus developability, and when added constraint or affinity costs a property that matters more

Judge the agent

- Interrogate agent reasoning step by step, and challenge conclusions that sound right but would not survive a project review or lab meeting

- Pinpoint where agents go wrong: why a step fails, what an expert would do instead, and what evidence would change the call

- Score agent confidence, rewarding explicit uncertainty over overconfident calls on ambiguous data

Requirements

- PhD in peptide chemistry, biochemistry, biophysics, structural biology, medicinal chemistry, or a related field

- Senior, hands-on peptide discovery experience: you have personally analyzed real program data, not just supervised it

- Direct 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)

- Deep expertise in at least one area (display and selection, biophysics, structural mapping, or peptide medicinal chemistry) and working fluency across the others

- Strong command of experimental design, quantitative data analysis in Python or R, and statistics

- AI-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

- Confidence to overrule an AI agent when the evidence demands it, and the openness to update when shown wrong

- Ability to calibrate confidence and communicate uncertainty rather than defaulting to binary calls

- Bonus: peptide format and chemistry experience, such as macrocyclization, hydrocarbon stapling, N-methylation, D- and non-canonical residues, or HELM encoding

- Bonus: 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

Culture @ Latch

How we work. We practice radical transparency: you’ll know how the company is doing, what’s working, and what isn’t. It’s always us against the problem, never each other. We’re respectfully opinionated, we respect each other’s time, and we think through possible solutions before we bring a problem to anyone. Most of the team arrives between 7 and 10am and leaves between 4 and 7pm. Nobody tracks when you’re in, but we give each other a heads-up on Slack when we’re running later than usual. We judge output, not time in a seat, and the only fixed meeting are a few pod check-ins per week. We use AI constantly, so we reward 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.

Outside of work. Company outings most months, team offsites, and a community that does cycling, soccer, figure skating, boxing, running, martial arts, music, books, and game nights.

Compensation & Logistics (US)

- Pay: $140K–$180K OTE, a mix of base & uncapped performance pay. Split varies by state. - Performance pay is based on weekly quota attainment. - If we pull you onto a special project, you’re paid full OTE for its duration. - If the platform goes down, you’re paid full OTE for that day.

- Ramp: full OTE for your first 4 weeks while we onboard you into our workflows.

- Employment: full-time W-2 - Health, dental, vision: 100% covered for you, 50% for dependents - 401(k) (no match) - PTO: 12 days to start, more as you’re promoted

- Growth: promotions are based on output, not tenure, with OTE rising at each level.

- Location: remote, hybrid, or onsite in SF. Onsite is preferred: waterfront office in Mission Bay, catered lunch and dinner, unlimited snacks.

- Work authorization: we sponsor H-1B (incl. transfers), O-1, TN, and support STEM OPT.

Interview Process

Timeline: We move fast: no longer than 2 week interview process

1. Apply

2. Take-Home Project HackerRank

3. Latch Intro - Talent Team

4. Technical Interview - Member of Technical Staff

5. Culture Interview - C-Suite

6. Offer

7. Background Check