Mercor
Fullstack Engineer, RL Environments
About this role
Mercor seeks a Senior Fullstack Engineer to lead the development of their internal platform, Studio, which is essential for data management and delivery for AI labs. The role requires expertise in both frontend and backend technologies to improve user journeys and operational efficiency.
What you'll do
- Oversee the Studio platform's full stack development.
- Set engineering best practices for frontend and backend systems.
- Develop foundational frameworks for data handling and task formats.
- Deliver impactful features to enhance data generation processes.
- Collaborate with cross-functional teams to clarify requirements.
What they're looking for
- 5+ years of fullstack engineering experience
- Proficiency in JavaScript/TypeScript, React, Next.js
- Backend experience in Python or Node.js
- Designing relational databases and REST APIs
- Strong usability and design sense
- Experience with high-throughput data systems
- High ownership mindset
- Excellent communication skills
Benefits
- Bi-annual performance bonus structure
- Generous equity grant vested over 4 years
Opens the application — the Jobs AI extension fills it for you. Set up autofill
Opens the official application on the employer’s site. No login required.
Mercor
Mercor builds a marketplace platform connecting expert talent to AI opportunities, supported by identity infrastructure, matching algorithms, and internal tools for data management. The company is hiring Software Engineers, Machine Learning Engineers, Fullstack Engineers, and Security Engineers to develop backend systems, ML models, cloud infrastructure, and distributed platforms.
- Website
- mercor.io
Likely interview questions
- Walk us through a complex fullstack feature you've shipped end-to-end. How did you approach the frontend architecture and backend design, and what tradeoffs did you make?
- Describe your experience designing APIs and data pipelines for high-throughput systems. How do you think about scalability and reliability when handling large data volumes?