Note: The job is a remote job and is open to candidates in USA. Surge AI is on a mission to raise AGI with the richness of human intelligence, founded by engineers and researchers aiming to build the next generation of AI. As a Software Engineer, Coding Evaluation & Training Data, you will own coding data projects that teach frontier models how to code, focusing on training data quality and system design rather than traditional product feature work.
Responsibilities
- Own end-to-end coding data projects, from initial scoping and pilot design through execution, iteration, and scale-up
- Design agentic training workflows and task structures that mirror real-world SWE work (e.g., refactoring, debugging, code review, large-repo navigation, tool use)
- Define and iterate on rubrics, golden sets, and reward signals that capture true engineering value, not just “does it compile.”
- Evaluate data and worker output with strong SWE taste, and make calls about what meets the bar for frontier training
- Design and run qualification processes for coding workers, including hands-on assessments of their coding ability
- Set up or partner on complex technical environments (e.g., containers, repos, test harnesses, sandboxes, code execution infrastructure)
- Partner with technical staff at our clients to translate high-level training goals into concrete projects and technical environments
- Collaborate closely with Surge engineering, product, and operations to improve our coding data products, internal tools, and execution processes
Skills
- 2–6+ years of professional software engineering experience building and maintaining real systems
- Strong coding ability in at least one mainstream language and comfort working in production codebases
- High “taste” for good engineering: you care about correctness, code quality, and how real engineering teams actually work
- Ability to reason about and debug technical environments, including containers, dependencies, and automated test setups
- Interest in owning projects end-to-end, including scoping, workflow design, execution, and continuous improvement
- Excellent written and verbal communication skills, with the ability to speak credibly with senior client engineers and translate fuzzy goals into actionable plans
- Excitement about AI/ML systems and the role of data, evaluation, and reward design in improving agentic coding capabilities
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