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About the Role
Contribute to the technical approach for evaluating AI agent reasoning in biological function, recovering and interpreting experimental evidence to make informed decisions about binding, stability, immune escape, viral fitness, toxin potency, and protein design. Build ground-truth benchmark datasets to rigorously test AI agent capabilities in quantitative reasoning steps, such as parsing noisy assay data, inferring mechanism, and predicting functional outcomes. Define how to measure agent capability in understanding and reasoning about biological sequences and structures through hands-on expertise in functional biology assays and computational modeling.
Responsibilities
- Contribute to the technical approach for evaluating AI agent reasoning in biological function.
- Recover and interpret experimental evidence to make informed decisions about binding, stability, immune escape, viral fitness, toxin potency, and protein design.
- Build ground-truth benchmark datasets drawn from real discovery and development programs.
- Rigorously test AI agent capabilities in quantitative reasoning steps, such as parsing noisy assay data, inferring mechanism, and predicting functional outcomes.
- Define how to measure agent capability in understanding and reasoning about biological sequences and structures.
Requirements
- Hands-on experience in biochemistry, biophysics, bioengineering, synthetic biology, virology, microbiology, immunology, or a closely related field.
- Direct experience generating or analyzing functional-assay data (titration curves, deep mutational scanning, potency assays, cell-based readouts, etc.) OR computational protein design.
- Comfort with quantitative modeling applied to noisy experimental data.
- Proficiency in Python and/or R for data analysis & visualization.
- Familiarity with binding affinity & stability (Tite-seq, SPR/BLI, biophysical characterization).
- Familiarity with immune escape & immunogenicity assessment.
- Familiarity with viral fitness, host-range, or zoonotic spillover evaluation.
- Familiarity with toxin potency or antimicrobial/antiviral resistance.
- Familiarity with protein design or structure-guided functional design.
- Familiarity with gain-of-function or molecular mechanism investigation.
- Experience designing or troubleshooting functional assays (ELISA, cell-based, biochemical).
- Familiarity with deep learning applied to protein design or functional prediction.
- Exposure to regulatory or safety considerations in bioengineering.
Skills
- Functional biology assays
- Computational modeling
- Python
- R
- Data analysis
- Data visualization
- Binding affinity & stability
- Immune escape & immunogenicity assessment
- Viral fitness, host-range, or zoonotic spillover evaluation
- Toxin potency or antimicrobial/antiviral resistance
- Protein design
- Structure-guided functional design
- Gain-of-function investigation
- Molecular mechanism investigation
- ELISA
- Cell-based assays
- Biochemical assays
- Deep learning
- Protein design prediction
- Functional prediction
- Regulatory considerations
- Safety considerations
Location
- China Basin, San Francisco
Work Type
- Full-time
- In-person
- Remote
Salary/Compensations
- OTE 120k - 180k - Performance based pay
Benefits
- Free meals onsite (lunch and dinner)
About the Company
- 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.