Research Engineer, Coding Evaluation & Training Data

The Role

As a Research Engineer, Coding Evaluation & Training Data at Surge, you'll sit at the intersection of software engineering and product to build and run the systems that teach frontier models how to code.

You’ll own end-to-end coding data projects for top AI labs, designing tasks, RL environments, and evaluation schemes that reflect real-world software engineering. This is an ideal role for a software engineer who wants to keep using their engineering skill set every day, but is most excited by training data quality, agentic evaluation, and system design (humans + models + tools) rather than traditional product feature work.

What You'll Do

• 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.

What We're Looking for

• 3-6+ 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.