Research Engineer, Coding Evaluation & Training Data

Summary

Surge AI is focused on building the next generation of AI with a mission to raise AGI with human-like intelligence. The Research Engineer, Coding Evaluation & Training Data role involves owning end-to-end coding data projects and designing workflows that reflect real-world software engineering tasks.

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

• 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

Qualifications

Must Haves

• 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