Staff Engineer, Reinforcement Learning Environments

Labelbox; San Francisco, Northern (CA, KY); Hybrid; USD 140,000 - 200,000; Full time

Job summary

Labelbox is seeking a hands-on engineer to build production‑quality RL environments and tooling. You will integrate with the RL tooling ecosystem and partner with our data operations team to keep environments robust and observable for annotators and model agents.

You’ll own environment deployment, CI/CD pipelines, and the ongoing prototyping of new environment types as client needs evolve. The role rewards ownership, rapid iteration, and clear metrics in a fast‑moving AI infrastructure team.

Qualifications

• 2+ years of professional software engineering experience
• Python fundamentals and at least one systems language (Go, Rust, or C++)
• Experience with containerization and sandboxing in production
• Familiarity with RL concepts and environments
• Experience building developer tooling or infrastructure automation
• Strong debugging across processes, containers, and networks
• Ability to read papers and implement from benchmarks

Responsibilities

• Develop reproducible, containerized execution environments (Docker, VMs, lightweight sandboxes) that support deterministic task rollouts and reward signal collection
• Integrate with and extend open‑source agentic tooling and custom CLI/API harnesses to enable multi‑step agent interaction
• Build instrumentation and observability layers—structured logging, trajectory capture, state snapshotting for auditable data
• Collaborate with data operations to design task curricula and evaluation protocols that stress‑test model capabilities across environment types
• Own environment deployment and reliability: CI/CD pipelines, automated testing of environment configurations, and monitoring for drift or breakage across versions
• Rapidly prototype new environment types as client and internal requirements evolve, moving from spec to working system in days, not weeks

Skills

Python

Go

Rust

C++

Debugging

Tools

Docker

Podman

Firecracker

Job description

Labelbox is seeking a hands-on engineer to build production‑quality RL environments and tooling. You will integrate with the RL tooling ecosystem and partner with our data operations team to keep environments robust and observable for annotators and model agents.

You’ll own environment deployment, CI/CD pipelines, and the ongoing prototyping of new environment types as client needs evolve. The role rewards ownership, rapid iteration, and clear metrics in a fast‑moving AI infrastructure team.