research
Posted Mar 25Research Engineer - Environments, Data and Post-Training
at Mercor
San Francisco, United StatesOn-site
sql$15,000
Responsibilities
- - Build and maintain data generation and augmentation pipelines that scale with training needs.
- - Create and refine rubrics, evaluators, and scoring frameworks that guide training and evaluation decisions.
Requirements
- ABOUT MERCOR Mercor's mission is to organize human intelligence to power the AI economy.
- We partner with leading AI labs and enterprises to provide the human intelligence essential to AI development.
- Our vast talent network trains frontier AI models in the same way teachers teach students: by sharing knowledge, experience, and context that can't be captured in code alone.
- Mercor is creating a new category of work where expertise powers AI advancement.
- You’ll work alongside researchers, operators, and AI companies at the forefront of shaping the systems that are redefining society.
- ABOUT THE ROLE As a Research Engineer at Mercor, you’ll work at the intersection of engineering and applied AI research.
- You’ll contribute directly to post-training and RLVR, synthetic data generation, and large-scale evaluation workflows that meaningfully impact frontier language models.
- Your work will be used to train large language models to master tool use, agentic behavior, and real-world reasoning in real-world production environments.
- WHAT YOU’LL DO - Work on post-training and RLVR pipelines to understand how datasets, rewards, and training strategies impact model performance.
- - Collaborate closely with AI researchers, applied AI teams, and experts producing training data.
- WHAT WE’RE LOOKING FOR - Strong applied research background, with a focus on post-training and/or model evaluation. - Strong coding proficiency and hands-on
- experience working with machine learning models. - Strong understanding of data structures, algorithms, backend systems, and core engineering fundamentals. - Familiarity with APIs, SQL/NoSQL databases, and cloud platforms. - Ability to reason deeply about model behavior, experimental results, and data quality. - Excitement to work in person in San Francisco, five days a week (with optional remote Saturdays), and thrive in a high-intensity, high-ownership environment.
- experience in industry (highest priority). - Publications at top-tier conferences (NeurIPS, ICML, ACL). -