Research Engineer, Coding Evaluation & Training Data

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.

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.

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.”