Mercor is training models that predict how well someone will perform on a job better than a human can. The company is experiencing hyper-growth and needs to scale its systems to support the world's leading AI companies.
Requirements
- Strong coding fundamentals in Python (our primary backend), though interviews are language-agnostic.
- Deep understanding of distributed systems, scalability challenges, and system design.
- Experience shipping production systems at scale in high-growth or high-stakes environments.
- Ability to reason about trade-offs and make decisions balancing speed and reliability.
Responsibilities
- Design, build, and scale production-grade backend APIs, services, and infrastructure.
- Take ownership of system design and architecture decisions that impact core workflows.
- Mentor and support junior engineers through code reviews, pair programming, and design discussions.
- Partner with Product and Design to deliver features quickly without sacrificing quality or scalability.
- Anticipate technical bottlenecks, propose solutions, and drive initiatives that increase reliability.
- Contribute to the systems that enable OpenAI, Anthropic, Google, and others to train and evaluate their models.
Other
- Set technical direction for high-impact initiatives.
- Help shape engineering culture, influence product decisions, and ensure our systems scale in lockstep with our hyper-growth.
- Strong communication skills with an ability to align technical and business goals.
- Bias toward ownership, curiosity, and delivering simple solutions to complex problems.
- Generous equity grant vested over 4 years
