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.