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Mercor is an AI data company on a mission to organize human intelligence to power the AI economy. The company operates at the intersection of human expertise and frontier AI models, with millions of domain experts on its platform contributing to AI training. Mercor is a profitable Series C company valued at $10 billion, operating offices in San Francisco, NYC, and London with a five-day in-person work culture.
As a Software Engineer on the Applied AI team, you'll build and operate systems that bridge frontier AI research and data delivery. This is a high-ownership, deeply technical role where you'll work through ambiguous problems, prototype quickly with researchers and customers, and scale systems from early experiments to reliable production.
Key responsibilities include partnering with frontier AI labs to understand their data, post-training, and evaluation needs; building and operating scalable data pipelines for post-training workflows and model evaluations; designing systems for synthetic data generation and data quality; prototyping new data types, benchmarks, and evaluation frameworks; and leading technical discussions with customers.
The role uniquely blends deep technical execution with customer interaction. You'll have direct exposure to cutting-edge AI research, working closely with leading AI labs on infrastructure that accelerates frontier research. The environment is fast-moving with high ownership, technically demanding collaborative work, and aligned with frontier research timelines.
Required qualifications include strong backend engineering fundamentals in modern languages (Python, Go, Rust, etc.), experience with model training and inference, strong grounding in statistical analysis and experimental design for measuring model performance, familiarity with LLM evaluation methods, and comfort working through ambiguity while shipping iteratively.
Ideal candidates enjoy ownership and customer-facing problem solving, think entrepreneurially and move quickly, balance speed with engineering rigor, and communicate clearly with technical and non-technical users. The role offers direct exposure to frontier AI research, real ownership with visible impact, technical depth paired with human interaction, and fast feedback loops with high leverage.
