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Mercor
New York, United States
Source: Mercor careers · View original posting
From Mercor's posting. “We” and “our” refer to the employer.
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.
As a Software Engineer on Applied AI
, you’ll build, deploy, and operate systems that sit directly between frontier AI research and data delivery.
This is a high-ownership, deeply technical role. You’ll work through ill-defined problems, prototype quickly with researchers and customers, and take systems from early experiments to reliable, scalable production. You’ll own projects end-to-end: spanning requirements gathering, creating data creation pipelines, and improving model-adjacent infrastructure, while partnering closely with frontier AI labs and Mercor’s internal teams to ship high-impact applied AI solutions.
Direct frontier exposure.
You’ll work closely with researchers at leading AI labs, building infrastructure that directly accelerates cutting-edge research.
Coding + customer work.
This role blends deep technical execution with customer interaction. Engineers who enjoy both building and communicating tend to thrive.
Day-to-Day
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