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Design and build multi-stage tasks to benchmark AI agents on real-world spatial transcriptomics projects. Evaluate agent decision-making processes across complex biological data workflows from image alignment to downstream inference.
As molecular data generation and frontier model intelligence grows, new approaches to data analysis are needed across the biotech industry. Latch is building intelligent, high-performance agents for biological data analysis, empowering over 5,000 scientists across 150+ R&D labs to handle data from instrument-to-insights.
We're seeking a Bioinformatics Engineer to join our Biosurveillance team, working at the frontier of what artificial intelligence can achieve in biology.
About the Role
You design tasks that test whether AI agents can work through real spatial transcriptomics projects. It's not about whether they can run a tool, it's whether they understand how decisions cascade. You pick how to align tissue images, which affects how you segment cell boundaries, which determines which unmixing method works, which shapes everything downstream. We're testing if they get that ripple effect. You'd be pulling from real published papers, building multi-stage tasks, and grading whether agents understand the why behind each choice, not just the mechanics.
Requirements
Systems thinking across spatial workflows: You understand how image preprocessing (tissue alignment, background removal) affects segmentation quality; why nucleus-level segmentation demands different deconvolution (RCTD, Tangram, SPOTlight, STRIDE) than spot-level data; when morphological features matter for downstream inference
Domain-specific judgment: You know the trade-offs between platforms (Visium's spots vs. MERFISH's near-cellular resolution vs. Xenium's high-plex imaging); when to deconvolve spots vs. when to segment first; how cell density and tissue morphology constrain method choice
Tool flexibility: You learn spatial tools (Baysor, STdeconvolve, giotto, Squidpy) and image-processing pipelines as needed
Task design: You build multi-checkpoint benchmarks where agents must handle registration failures, justify segmentation thresholds, and defend deconvolution assumptions in tissues with variable morphology
Culture @ Latch
How we work. Genuinely flexible schedules, we just ask that you communicate when you're coming in later than usual. We care most about hard work and output. We're respectfully opinionated, it will always be us against problems, not each other. Optimize for each other's time and bring solutions, not just problems. You'll join a bench suited to your expertise, but we value cross-domain learning and interoperability across teams.
The office & perks. Waterfront office near Oracle Park, 2x free daily meals, unlimited snacks, company outings most months, and team offsites. Plus a vibrant team: cycling, soccer, figure skating, boxing, run clubs, reading clubs, martial arts, music, game nights.
Compensation & Logistics
1099 (or W8-BEN) contract, 40 hrs/week, no end date
Fully performance-based pay: $120K–$180K, uncapped upside. 2x quota = 2x pay.
2-4 week paid ramp - full OTE from day one
Remote (globally), hybrid, or onsite in SF (onsite preferred)
Work authorization: OPT visa holders only (not STEM Extension)
Onsite perks: 2x free meals/day, waterfront office (China Basin), monthly parking (based on availability)
Candidates with all of the above qualifications + proven management skills will be eligible for more senior positions
Interview Process
Timeline: We move fast: 8–12 days from submission to offer.
Intro Screen - Technical Recruiter
Take-Home Project - HackerRank
Technical Interview - Member of Technical Staff
Culture Interview - C-Suite (If applicable)
Offer
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