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.
Evaluate AI-generated responses for scientific accuracy and logical consistency.
Test AI models with theoretical biology questions and realistic laboratory scenarios.
Identify and document model failure modes, recommending improvements to prompts and evaluation methods.
A partner company of Jobgether focused on improving AI language models through expert scientific training and evaluation. The organization works with freelance specialists to enhance AI reasoning and reliability in biological domains.
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.
Evaluate complex chemistry problems and provide scientifically accurate solutions.
Review technical scientific texts for accuracy and clarity.
Provide domain-specific annotations on specialized chemical datasets and navigate an asynchronous platform to complete expert tasks.
Terac is building the world's largest pool of vetted human experts for AI. Researchers, AI labs, and product teams use Terac to recruit, screen, and pay study participants across industries, languages, and skill sets.
Develop agentic research systems to automate mechanistic model development for biochemical and physiological processes.
Design and train machine learning models for in-context learning and few-shot adaptation on molecular and tabular data.
Collaborate with chemists and biologists to drive drug discovery decisions using AI models.
PostEra is building an AI-first biotech, using its Proton AI platform to accelerate the discovery of new medicines for patients. The company has a minimalist organizational structure, celebrating individual achievement through proportional compensation and collaboration toward delivering cures.
Design realistic healthcare and medical tasks that challenge advanced AI agents.
Analyze clinical records, research findings, and healthcare data to identify inconsistencies and errors.
Develop reference solutions and evaluation criteria for AI-generated medical analyses.
Anyone AI creates high-quality training and evaluation data for frontier AI models. The company offers flexible, remote contract work focused on expert-driven AI evaluation and improvement.