Bioinformatics Engineer — Single-Cell AI
About The Position
At LatchBio, our AI agents help thousands of scientists analyze and interpret data across the full stack of modern multi-omic technologies — starting with single-cell and spatial, and expanding fast. We're building the ground truth for AI in single-cell biology. Our benchmark scBench — 394 verifiable problems across six sequencing platforms — shows the best frontier model today still fails nearly half the time. We're hiring bioinformatics engineers to close that gap: scientists who can turn real experimental data into the precise, falsifiable questions that define what it means for an AI agent to actually understand scRNA-seq.
Requirements
- Experience with end-to-end data analysis for one or more of the following sequencing platforms: MissionBio, ParseBio, CSGenetics, BD Rhapsody, Illumina, or 10X Chromium
- Analyzed 3+ datasets from raw data to end insight for either publications or industry experiments with real world consequences
- Working understanding of platform-specific quality control thresholds and intuition for numerical examples of positive or negative results (e.g., 100K cells from a ParseBio run with 80% mitochondrial reads means something is wrong)
- Familiarity with the landscape of computational biology tools for scRNA-seq tasks (e.g., Scanpy/Seurat for core workflows, cell typing frameworks like CellTypist or Azimuth, DE methods like DESeq2 or edgeR)
- Strong understanding of experimental design, hypothesis generation and scientific conclusions from papers using one of the sequencing platforms described
- Ability to distill an analysis step into a precise, falsifiable biological question with a single defensible answer
- Working understanding of concepts in statistical inference: hypothesis testing, confidence intervals and/or estimators
- Working understanding of important algorithms in high dimensional data analysis: e.g. PCA, neighborhood graphs, UMAP, clustering methods (Leiden/Louvain)
Nice To Haves
- Published research that relied on modern single-cell RNA sequencing techniques.
- Engineered tools or packages in the single-cell biology domain.
- Experience generating training data for AI agents or foundation models.
Responsibilities
- Own end-to-end scRNA-seq analyses across multiple projects: raw platform outputs → QC and failure diagnosis → normalization → dimensionality reduction → clustering → cell typing → differential expression → trajectory analysis → defended biological claim.
- Build reproducible workflows and produce clear decision traces: what was filtered, why, what changed the conclusion, what would falsify the claim.
- Distill analysis steps into precise, falsifiable biological questions with single defensible answers — the core unit of our eval suite.
- Debug platform and data issues with precision: turn messy results across diverse sequencing chemistries into crisp hypotheses, sanity checks, and a stepwise debugging plan.
Benefits
- $130k–$180k/yr (performance-based)
- Equity
- Unlimited PTO (truly)
- Waterfront office in China Basin, San Francisco
- Free lunch and dinner
- 100% premium covered on Blue Shield's platinum health plan ($0 premium, $0 deductible)
- 401(k) plan options
- Work visa sponsorship
- Company-sponsored professional development
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
