Research Operations, Code

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.

In the Research Operations role at Mercor, you will work at the intersection of engineering and applied AI research. This role will own multi-million-dollar data programs end to end with responsibilities to:

• Reason about opportunities for frontier coding models, and translate that into the data that will make it stronger.

• Shape how data gets produced, including human-expert workflows, synthetic generation pipelines, and model-in-the-loop systems.

• Turn designs into scaled, high-quality data pipelines and own deliveries to customers.

• Build deep relationships with lab researchers and become the person they trust to tell them what data they actually need.

• Bachelor’s degree in Computer Science, a STEM field, or an equivalent technical discipline.

• At least two years of experience in software development or a forward deployed engineering role.

• A track record of running complex, high-stakes projects end to end, and genuine energy for large-scale execution and gritty process optimization under pressure.

• Strong analytical and communication skills; comfortable owning high-profile relationships with technical customers.

• Experience designing scalable data or automation pipelines

• Research fluency: connecting model/benchmark literature to what data would move a frontier model; having created a benchmark or published analysis of model behavior.

• Backgrounds that often fit: data scientists, software engineers, or forward deployed engineers who love operating, technical PMs, research engineers, or strong generalist operators with real technical range. Backgrounds from consulting, finance, or high-growth startups can work if paired with real technical fluency.