Harmonize your Wet and Dry Lab. Backed by Lux.
About the role
We’re seeking an AI Biologist to join our TxBench team, pushing what AI can achieve in therapeutic antibody development. Found on 1752vc Careers, the job board for startup and VC roles.
What they're looking for
- PhD in protein engineering, biochemistry, analytical chemistry, pharmacology, or a related field
- Hands-on analysis of antibody development data. You’ve done the analysis yourself, not just supervised it
- Deep expertise in at least one area (analytical/CMC characterization, large-molecule DMPK, protein engineering and developability, or non-clinical safety) and working fluency across the others
- Command of how readouts map to critical quality attributes, PK and effector properties, and release or comparability decisions
- Python or R for data analysis, including parsing chromatograms and electropherograms, kinetic fitting, or PK modeling
- AI-ready from day one: daily use of Claude, Cursor, or similar agents, with the judgment to spot where model reasoning is technically correct but scientifically unsound
More about this role
Latch builds rigorous scientific benchmarks ( benchmarks.bio ) for AI agents across biology. We work with frontier labs and pharma to measure whether agents can handle real biological workflows: the messy, multi-layer reasoning that matters in the field.
We’re seeking an AI Biologist to join our TxBench team, pushing what AI can achieve in therapeutic antibody development.
About the Role. You will be the scientific authority on ground truth, testing whether agents can reason like an expert biologics development scientist. The benchmark covers monoclonal antibodies, Fc-fusions, and bispecifics in the window after lead nomination and before IND. AI agents today struggle to interrogate raw analytical traces and preclinical data, separate real quality-attribute failures from analytical artifacts, and make advance, engineer, or kill calls an expert would stand behind. You will work with software engineers and scientists to build the tasks and datasets behind our benchmarks. Your judgment will set the standard agent outputs are held to, including:
Turn real development workflows into file-based tasks with structured outputs and deterministic grading: developability triage,...
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