---
title: 'AI Neuroscientist at LatchBio'
canonical: 'https://feeny.ai/job/ai-neuroscientist-latchbio-san-francisco-9zp5zbsy4dty'
type: 'job'
last_seen: '2026-10-20'
---

# AI Neuroscientist at LatchBio

- **Company:** LatchBio
- **Location:** San Francisco, CA
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2026-10-13
- **Last confirmed live:** 2026-10-20
- **Apply:** https://jobs.ashbyhq.com/latchbio/08d47716-b878-4364-ba31-79ec681ec14c

## Job description

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. 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.

## Compensation & Logistics

- Contract: 1099 (or W-8BEN internationally), no end date
- Pay: 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.
- Commitment: full-time, on your own schedule. Most of the team works 40+ hours a week.
- Meetings: a few pod check-ins a week. The rest of your time is yours.
- Location: remote (anywhere), hybrid, or onsite in SF. We prefer onsite.
- Onsite perks: catered lunch and dinner daily, a waterfront office in Mission Bay, and monthly parking when available
- Work authorization: US citizens, permanent residents, and OPT holders. We can’t support STEM OPT extensions or sponsorship.

Interview Process We move fast: about 2–3 weeks from your first call, to offer.

- Intro Screen - Latch Talent Team
- Take-Home Project - HackerRank
- Technical Interview - Member of Technical Staff
- Culture Interview - C-Suite
- Offer

## About LatchBio

## Company Overview
- **One-liner**: LatchBio builds and deploys frontier AI agents for biological data analysis, serving over 300 biopharma and R&D labs worldwide.
- **Entity Type**: Private (Series A; total funding $33.2M)
- **Headquarters**: San Francisco, California, United States
- **Founded**: 2021
- **Founders**: Alfredo Andere (CEO) and Kenny Workman (CTO)

## Core Business
- Primary industry: Biotechnology Research / AI for biology
- Target customers: B2B – biopharma companies, academic R&D labs, and solution providers (kits, assays, instrument vendors)
- Mission: Deploy AI agents into real scientific work to accelerate data analysis and drug discovery

## Products & Services
- **Latch Platform**: A unified, serverless bioinformatics platform that lets scientists run, track, and debug pipelines via an SDK-generated no-code interface. Supports FastQ, CSV, H5AD, TIFF, and other formats. Agents can analyze messy real-world data.
- **Latch SDK**: Python toolchain to define serverless workflows and dynamically generate no-code UIs, removing cloud-infrastructure overhead.
- **agent.bio**: Public, interactive sandbox where frontier AI agents (e.g., Claude 4.8 Opus) analyze biological data. Supports 40+ solution providers.
- **benchmarks.bio**: Open, reproducible benchmarks measuring AI agent performance on spatial, single-cell, epigenomics, and preclinical pharmacology data. Includes papers like scBench-Long, TxBench-PP, etc.
- **White-labeled data analysis**: Solution providers can offer a branded, simpler analysis experience for their kits and services.

## Market Standing
- **Valuation/Market Cap**: Not publicly disclosed
- **Key Metric**: Annual revenue of ~$1.0M (LinkedIn estimate); total funding $33.2M
- **Notable Investors/Partners**: Coatue, Lux Capital, Fifty Years, Haystack, Gelt, Backend Capital; individual investors include George Church, Jeff Dean, Hemant Taneja, Laura Deming, Alec Nielsen
- **Growth Signals**: 140% YoY headcount growth (from ~11 to 26 employees); 300+ biopharma and academic teams served; 40+ solution providers onboarded; recent publication of multiple benchmark papers (2025–2026)

## Competitive Advantages
- **First-mover in AI agents for biology**: Combines frontier LLMs with rigorous, verifiable benchmarks tailored to biological data (spatial, single-cell, epigenomics, pharmacology).
- **Open benchmarks & reproducibility**: All benchmarks (e.g., scBench-Long) are published openly, building trust and attracting top talent.
- **White-labeling for solution providers**: Allows kit and instrument vendors to offer AI-powered data analysis under their own brand, creating a network effect.
- **Tight integration with real lab workflows**: Supports common file formats and interfaces with existing pipelines, reducing friction for scientists.

## Strategic Focus
- Continue research and deployment of AI agents for biology, with emphasis on long-horizon tasks and messy real-world data.
- Expand the agent.bio sandbox to more solution providers and biopharma customers.
- Publish additional benchmarks (spatial, preclinical) to establish Latch as the standard evaluator of AI in biology.
- Grow engineering and bioinformatics teams to accelerate platform development.

## Why Work Here
- **Engineering culture**: Small, high-autonomy team where engineers own features end-to-end and see their code impact thousands of scientists the same day. Reading groups on category theory, immunology, and more.
- **Remote/hybrid policy**: Not explicitly stated, but headquarters in San Francisco; office parking subsidized. Likely in-office with flexibility.
- **Notable perks**: Unlimited PTO, 100%-subsidized platinum health plan (Cigna) + 75% for dependents, dental/vision, 401(k), ambitious equity, 12+ meals weekly, annual tech stipend, signing bonus, O-1 visa sponsorship, professional development.
- **Team size**: ~26 employees, with 65% in technical roles (engineering, bioinformatics, research). Flat structure with direct access to founders.
- **Growth trajectory**: Rapid headcount growth and expanding customer base offer career acceleration opportunities.

## Sources
1. [latch.bio](https://latch.bio/)
2. [latch.bio/about](https://latch.bio/about)
3. [linkedin.com/company/latchbio](https://www.linkedin.com/company/latchbio)
4. [cbinsights.com/company/latch-bio](https://www.cbinsights.com/company/latch-bio)
5. [jobs.ashbyhq.com/latchbio](https://jobs.ashbyhq.com/latchbio)

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