Software Engineer, Coding Evaluation & Training Data
- Role
- AI / ML
- Experience
- Mid
- Employment
- Full-time
Open to US only. Set where you work from to check your eligibility.
No BS summary
Software engineer with 2–6+ years building real systems, strong coding ability, and comfort in production codebases. Must be US-based remote and interested in AI coding evaluations, training data quality, RL environments, and reward design.
Required skills
ABOUT US
Our mission is to raise AGI with the richness of human intelligence — curious, witty, imaginative, and full of unexpected brilliance.
Surge was founded by engineers and researchers who dreamed of building the next generation AI. We're building a platform that powers the most powerful models in the world in partnership with companies like, Anthropic, Google, Microsoft, and Meta.
At Surge, we believe the path to AGI isn't just about scaling compute—it's about embracing the unlimited ceiling of human intelligence and creativity in the data that shapes these systems. Our platform combines elite human expertise with cutting-edge tools for scalable oversight, from building rich RL environments to conducting rigorous evaluations that go beyond benchmarks. We've run a profitable business from day one without raising venture funding.
THE ROLE
As a Software 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
- 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.
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 software engineering work such as refactoring, debugging, code review, large-repo navigation, and tool use.
- Define and iterate on rubrics, golden sets, and reward signals that capture true engineering value beyond whether code compiles.
- Evaluate data and worker output with strong software engineering judgment and decide 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 such as containers, repositories, test harnesses, sandboxes, and code execution infrastructure.
- Partner with technical staff at clients to translate high-level training goals into concrete projects and technical environments.
- Collaborate with Surge engineering, product, and operations to improve coding data products, internal tools, and execution processes.
What they require
- 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, including correctness, code quality, and how real engineering teams 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.
Surge is building a platform that powers AI models in partnership with companies like Anthropic, Google, Microsoft, and Meta, combining human expertise with tools for scalable oversight, RL environments, and evaluations.