You will shape how AI agents are evaluated in immunology by contributing to the technical approach and benchmark design.
You will build ground-truth datasets from studies, your own experience, and novel work to test expert-level reasoning.
You will collaborate with software engineers and computational biologists to rigorously measure agent performance on real biological tasks.
Latch builds rigorous scientific benchmarks for AI agents in biology, working with frontier labs and pharma to measure real biological workflows. The culture emphasizes radical transparency, heavy AI use, and original expert judgment, with a collaborative team that enjoys outings, sports, and game nights.
Set the scientific ground truth for TxBench, building file-based tasks and datasets across therapeutic antibody development workflows.
Test whether AI agents can distinguish real quality-attribute failures from analytical artifacts across CMC, PK, immunogenicity, and safety.
Interrogate agent reasoning step by step, score confidence, and make expert go/no-go calls that hold agents to development-review standards.
Latch builds rigorous scientific benchmarks for AI agents across biology, working with frontier labs and pharma. The culture is radically transparent, AI-driven, and rewards original expert judgment, with regular team outings and a preference for onsite collaboration.
Define expert reasoning for peptide discovery and write gold-standard answers with defended rationale.
Curate datasets from real programs and build Python analysis pipelines that produce verifiable ground truth.
Test and challenge AI agents' reasoning, scoring confidence and pinpointing where they go wrong.
Latch builds rigorous scientific benchmarks for AI agents across biology, working with frontier labs and pharma to measure real biological workflows. It's a transparent startup that uses AI constantly and rewards original expert judgment.
Serve as the scientific authority on ground truth for AI agents in neuroscience, testing expert-level reasoning across all system levels.
Build benchmark tasks and datasets for normal function and disease, curating multi-modal data and writing gold-standard expert answers.
Set hard calls on contested claims and interrogate agent reasoning, challenging fluent but unsound conclusions.
Latch builds rigorous scientific benchmarks for AI agents across biology, working with frontier labs and pharma to test whether agents can handle real biological workflows. The culture is radically transparent, opinionated but respectful, with structured autonomy, regular outings, and a preference for onsite work in SF.
Design challenging scientific evaluations that test AI agents' reasoning in human physiology.
Analyze real experimental, clinical, and physiological data to establish reliable ground truth.
Collaborate across disciplines, using AI-assisted tools to accelerate benchmark development.
Latch builds rigorous scientific benchmarks for AI agents across biology, working with frontier labs and pharma to measure real biological workflows. They practice radical transparency, reward original expert judgment, and foster a community with outings, off-sites, and shared activities.
Contribute to the technical approach for evaluating AI agents in diagnosing, treating, and researching rare and progressive diseases.
Build ground-truth benchmark datasets from studies and novel work that rigorously test agents' analytical and interpretive skills.
Collaborate with scientists, physician-scientists, engineers, and computational biologists to define strategy across multiple benchmarks.
Latch builds rigorous scientific benchmarks for AI agents across biology, measuring whether agents can handle real biological workflows. An early, tight-knit team, Latch practices radical transparency, uses AI constantly, and fosters a culture of respect, expert judgment, and community activities.
Contribute to the technical approach for evaluating AI agent performance across the genetic medicines pipeline, including gene therapy, gene editing, and RNA therapeutics.
Design realistic program case studies spanning target validation, drug design, screening, chemistry optimization, and IND-enabling studies.
Review and stress-test AI agent outputs for scientific soundness, calibrating confidence on preclinical data with incomplete or conflicting signals.
Latch builds rigorous scientific benchmarks for AI agents across biology, working with frontier labs and pharma to measure whether agents can handle real biological workflows. The culture emphasizes radical transparency, high agency, and using AI tools with original expert judgment.