AI Neuroscientist
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 Neuroscientist to join our Neuroscience team, pushing what AI can achieve in neuroscience.
About the Role. You will be the scientific authority on ground truth, testing whether agents can reason like an expert neuroscientist. AI agents today struggle to interrogate raw evidence across molecular, cellular, circuit, tissue, and behavioral levels, separate real effects from artifacts and confounds, and reach conclusions and R&D decisions an expert would stand behind. You will work with software engineers and neuroscientists to build the tasks and datasets behind our benchmarks across normal nervous-system function and disease; your judgment will set the standard agent outputs are held to, including:
Build the task
- Define what expert reasoning looks like for a research question or R&D decision, and write gold-standard answers with the rationale an experienced neuroscientist would defend
- Design realistic research scenarios across the workflow, from hypothesis and target selection through model-system choice, experimental design, data processing, and inference
- Curate multi-modal data bundles (electrophysiology, calcium imaging, EEG/sEEG, MRI/PET, single-cell and spatial transcriptomics, histopathology, behavior, biofluid markers)
- Pair basic-science and disease tasks (e.g., hippocampal replay in health and its disruption in epilepsy or Alzheimer’s disease) to test whether an understanding of normal function transfers to pathology
- Partner with software engineers to turn your judgment into new workflows
Set the hard calls
- Test whether agents choose the right model system and unit of analysis, and recognize when rodent, iPSC, or organoid findings will not translate to human disease
- Adjudicate contested claims in the literature: decide what the data supports, what they do not, and which experiment would settle the question
Judge the agent
- Interrogate agent reasoning step by step, and challenge conclusions that are fluent and textbook-correct but would not survive lab meeting, peer review, or a go/no-go decision
- Pinpoint where agents go wrong: state 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 binary calls when evidence is incomplete
Requirements
- PhD or MD/PhD in neuroscience or a closely related field
- Hands-on neuroscience research experience with first-hand data analysis and a publication record
- Direct experience analyzing raw data in at least two modalities: electrophysiology (patch-clamp, MEA, Neuropixels), optical imaging, EEG/sEEG, neuroimaging, single-cell or spatial omics, neuropathology, or quantitative behavior
- Deep expertise in at least one area (systems/circuit, cellular/molecular, clinical/translational, or computational neuroscience) and working fluency across system levels
- Strong command of experimental design and statistics
- Proficiency in AI agent use, with the judgment to identify 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
- Practical understanding of model systems (iPSC neurons, organoids, rodents, NHP, human cohorts)
- Familiarity with core resources is a plus: Allen Brain Cell Atlas/BICAN, DANDI/NWB, OpenNeuro/BIDS, IBL, ADNI, PPMI, UK Biobank, ClinVar/gnomAD
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
- Apply
- Take-Home Project HackerRank
- Latch Intro - Talent Team
- Technical Interview - Member of Technical Staff
- Culture Interview - C-Suite
- Offer
- Background Check