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Bioinformatics Engineer — Spatial AI

LatchBio

LatchBio

Software Engineering, Data Science
San Francisco, CA, USA
USD 130k-185k / year + Equity
Posted on Mar 22, 2026

Location

San Francisco

Employment Type

Full time

Location Type

On-site

Department

Bioinformatics

Bioinformatics Engineer — Spatial AI

At LatchBio, our AI agents help 4,000+ scientists analyze and interpret data from the next generation of spatial and multi-omic tools in biotech.

We are seeking bioinformatics engineers with computational and experimental expertise in spatial biology to help pioneer a new category of agentic analysis tools.

What you'll do

  • Own end-to-end spatial transcriptomics analyses across multiple projects: raw platform outputs → QC and failure diagnosis → cell segmentation and assignment → cell typing → DE/enrichment → spatial inference → defended biological claim.

  • Build reproducible workflows and produce clear decision traces: what was filtered, why, what changed the conclusion, what would falsify the claim.

  • Perform spatial reasoning beyond standard clustering: neighborhood and adjacency enrichment, spatial gradients and niches, spatial DE, and spatial autocorrelation-aware analyses.

  • Debug platform and data issues with precision: turn messy results into crisp hypotheses, sanity checks, and a stepwise debugging plan.

Requirements (must-have)

  • Experience with end-to-end data analysis for one or more of the following spatial technologies: Seeker or Trekker (Slide-seq), MERFISH, DBiT-seq, Xenium, Visium, Stereo-seq, GeoMx, CosMx, or other similar assays

    • Analyzed 3+ datasets from raw data to end insight for either publications or industry experiments with real world consequences

    • Working understanding of kit specific quality control thresholds and intuition for numerical examples of positive or negative results (eg. 100K cells from 10X Chromium means something is wrong)

    • Familiarity with the landscape of computational biology tools for spatial specific tasks (eg. cell segmentation, cell typing, ligand-receptor analysis)

Desired experience (nice-to-have)

  • Published research that relied on modern spatial biology techniques.

  • Engineered tools or packages in the spatial biology domain.

  • Experience generating training data for AI agents or foundation models.

Ideal candidate

You are a scientifically fluent engineer bridging experimentation and computation. You're comfortable being wrong, updating beliefs with evidence, and writing down decisions so others can reproduce and critique your work. You communicate clearly and take ownership of end-to-end solutions.

Compensation & benefits

  • $130k–$185k/yr (performance-based)

  • Equity

  • Unlimited PTO

  • Waterfront office in China Basin

  • Free lunch and dinner

  • 100% premium covered on Blue Shield's platinum health plan ($0 premium, $0 deductible)

  • 401(k) plan options

  • Company-sponsored professional development

  • Work visa sponsorship

  • Team-wide science reading groups

Full-time preferred, part-time available.
In-person in San Francisco preferred, remote options available.

About the team

We work on serious problems at the most important intersection in history: biology and AI. We are building a team of world-class people, and are all eager to dedicate a substantial part of our life to solving these problems.

If we succeed we will hugely accelerate scientific progress and aid the creation of therapies for cancer, solutions to global warming, and cures for aging.

Who you'll work with

How to apply

Apply on our Ashby posting here.

Hiring process

Our process moves quickly, typically completed within one week.

  • Round 0: Apply with a resume and cover letter

  • Round 1: Introduction — Saul (Technical Recruiter)

  • Round 2: Culture — Jordan (Chief of Staff) or Kyle (COO)

  • Round 3: Take-home — Zhen and Harihara (Bioinformatics)

  • Round 4: Technical — Kenny (CTO)

  • Offer

Learn more

Explore our products, read our papers, and engage with our team.

  1. Agent.bio — The AI agent for biology

  2. Benchmarks.bio — The benchmarks for biology agents

  3. Console.latch.bio — The harness for agentic data analysis