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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 for Therapeutics to join our therapeutics bench, working at the frontier of what artificial intelligence can achieve in biology.
About the Role
You will contribute to our technical approach for evaluating how AI agents reason through complex biologics therapeutics datasets. Working with software engineers and biologists, you'll build ground-truth benchmark datasets—drawn from real antibody and protein discovery programs—that rigorously test whether agents can perform the critical decision-making steps that human scientists execute.
Your hands-on expertise in variant ranking, enrichment analysis, and advancement prioritization will define how we measure agent capability in therapeutic discovery.
Requirements
2+ years hands-on experience with biologics discovery or development (antibody engineering, protein engineering, or cell/molecular biology-driven target validation)
Experience interpreting binding kinetics (SPR/BLI), biophysical stability data, and/or cell-based potency assays
Proficiency in Python and/or R for data analysis & visualization
Familiarity with at least one of:
Antibody optimization (CDR engineering, VH/VL pairing, variant screening)
Protein structure (AlphaFold, cryo-EM, docking)
High-throughput antibody/binding screens
PK/PD modeling for biologics (target occupancy, half-life, clearance) -
Bioprocess/manufacturability constraints
Nice-to-Have
Experience with immunogenicity risk assessment
Hands-on work with potency assay design (ELISA, cell-based, biochemical)
CMC/GMP-adjacent knowledge
Compensation & Logistics
OTE 120k - 180k - Performance based pay
Free meals onsite (lunch and dinner)
Waterfront office in China Basin, San Francisco
Full-time, in-person (can be remote)
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