About Mercor
Mercor's mission is to organize human intelligence to power the AI economy. We're a leading AI data company, building the layer between human expertise and frontier models. Millions of domain experts on the platform are paid over $4 million per day to train frontier AI models. Mercor's APEX benchmark family measures AI's real-world impact on professional work. Mercor Enterprise brings this same infrastructure to Fortune 500 companies: helping companies capture how their best people actually work, translating that expertise directly back into agents.
Mercor is creating a new category of work where expertise powers AI advancement. Achieving this requires an ambitious, fast-paced and deeply committed team. You’ll work alongside researchers, operators, and AI companies at the forefront of shaping the systems that are redefining society. Mercor is a profitable Series C company valued at $10 billion. We work in-person five days a week in our San Francisco, NYC, or London offices.
Mercor AI Capability Research Grants $5M
One of the biggest challenges facing the industry today is determining whether frontier AI is capable enough to deliver value in real-world settings. A model can perform well on benchmarks and still struggle in production. That’s why investing in capabilities research, realistic evaluations, and robust verification is critical.
Mercor is committing $5 million to fund AI capabilities research. The grant supports:
The time of experts from Mercor's platform
Researcher hours
API credits
Stipends for event and conference attendance
This is separate from the Mercor Research Fellowship, which funds individual experts (apply HERE) and our $5m of safety funding awards (apply HERE).
What we're looking for
Real-world evaluations: measuring whether benchmark performance translates into reliable performance on realistic tasks and workflows
Environments: building high-fidelity, interactive environments that capture the complexity of real-world work
Long-horizon tasks: evaluating and improving models’ ability to plan, execute, and adapt across extended workflows
Agentic capabilities: tool use, coordination, memory, and autonomous execution
Reasoning and problem-solving: improving performance on complex, ambiguous, or underspecified tasks
Post-training: developing better data, rewards, and training methods to improve model capabilities
Evaluation methodology: creating more robust measures of capability, reliability, and real-world utility
Why us
Funding for autonomous frontier-work.
Access to Mercor's expert network for human grading and annotation: lawyers, accountants, engineers, scientists, clinicians
Access to Mercor's internal evaluation infrastructure, subject to review
Introductions to Mercor's network of researchers across frontier labs and academia
Who should apply
Academic groups, independent researchers, and non-profit organizations
People with a specific, well-scoped question: the grant is built around your proposal, not a generic research rotation
Bonus: researchers with experience with agentic evaluation, RL environments, and post-training.
We expect grantees to publish – such as a paper, an open dataset, a public methodology, or a tool the field can use.
How to apply
Submit an Expression of Interest. We expect to see a one- or two-page document. It should contain at least a section on your team, background, and research accomplishments; a section on your proposed research project; and a section on the outputs and impact of the project, with directionally correct timelines and resource requirements.