Coding RL Engineer

Clera Labs, Inc.; San Francisco (CA); Remote; USD 180,000 - 260,000; Full time

Job summary

Clera Labs, Inc. is seeking a Coding RL Engineer to join the reinforcement learning team. You will turn real-world software work into reproducible benchmarks and build coding environments for training and evaluating advanced models.

You will convert production codebases into containerized environments, create tasks from real development activities, and help strengthen verifiers and benchmarking tools with research collaboration.

Qualifications

• 2+ years of professional software engineering delivering software systems.
• Strong Python skills and fluency in another language such as TypeScript, Go, Java, or Rust.
• Hands-on Docker experience and familiarity with reproducible build/test environments.
• Experience navigating unfamiliar, complex codebases and getting them building, running, and tested.
• Knowledge of coding model training and evaluation (SWE-bench-style tasks, code evaluations, RLVR).
• Experience creating coding tasks from real engineering work and hardening verifiers against flaky tests.

Responsibilities

• Convert licensed production codebases into reproducible, containerized coding environments.
• Create tasks from issues, PRs, commit histories, and incident records.
• Build verifiers with hidden tests and rubric- or model-based grading.
• Run model rollouts, review traces, and fix broken or ambiguous tasks.
• Contribute tasks and analysis to coding benchmarks and tooling for faster task creation.
• Collaborate with research teams to calibrate task difficulty and benchmark coverage.

Skills

Python

TypeScript/Go/Java/Rust

Docker

Codebase navigation

RL/ML knowledge

Tools

Docker

Job description

About the Role

Join an early-stage AI company as a Coding RL Engineer, working with the reinforcement learning team to build coding environments and tasks for training and evaluating advanced models. You will turn real-world software engineering work into reproducible benchmarks that help improve coding AI.

What You'll Do

• Convert licensed production codebases into reproducible, containerized coding environments.

• Use issues, pull requests, commit histories, and incident records to create tasks covering bug fixes, features, refactors, testing, and multi-file agent work.

• Build and improve verifiers with hidden tests, rubric-based or model-based grading, and safeguards against reward hacking and answer leakage.

• Run model rollouts, review traces, and repair or remove tasks that are broken, ambiguous, too easy, or exploitable.

• Contribute tasks and analysis to coding benchmarks and build tools that speed up task creation and validation.

• Work with research teams to calibrate task difficulty and benchmark coverage.

What We're Looking For

• At least 2 years of professional software engineering experience delivering software systems.

• Very strong Python skills and fluency in another language such as TypeScript, Go, Java, or Rust.

• Hands-on Docker experience and familiarity with reproducible build and test environments.

• Experience navigating unfamiliar, complex codebases and getting them building, running, and tested.

• Working knowledge of coding model training and evaluation, including SWE-bench-style tasks, code evaluations, RLVR, and agent harnesses.

• Experience creating coding tasks from real engineering work and hardening verifiers against flaky tests, unclear requirements, and leaked solutions.

• Relevant experience with frontier AI labs, evaluation teams, RL environments, coding agents, or large enterprise and legacy codebases is helpful.

Location

Remote within the United States or in person in San Francisco, California.