Staff Software Engineer — RL Environments & Tools

Labelbox; San Francisco (CA); On-site; USD 140,000 - 200,000; Full time

Job summary

Labelbox, the AI data platform, is hiring a Member of Technical Staff to own the design, development, and production of frontier data products. You will build the sandboxed, reproducible environments AI agents rely on during training and evaluation, the terminals, browsers, and tool-augmented workspaces they operate inside.

This is a hands-on engineering role. You’ll write production-quality infrastructure, integrate with the broader RL tooling ecosystem, and partner closely with our data

Qualifications

• 2+ years of professional software engineering experience.
• Strong fundamentals in Python and at least one systems-level language (Go, Rust, C++).
• Experience with containerization and sandboxing in production or near-production contexts.
• Familiarity with RL concepts and developer tooling/infrastructure automation.

Responsibilities

• Design, build, and maintain sandboxed RL environments for agentic AI training.
• Develop reproducible, containerized execution environments (Docker, VMs).
• Integrate with open-source agentic tooling and CLI/API harnesses.
• Build instrumentation and observability layers for auditable training data.
• Collaborate on curricula and evaluation protocols; ensure reliability across versions.
• Own environment deployment, CI/CD pipelines, and monitoring for drift.

Skills

Python

Go

Rust

C++

Containerization

Sandboxing

RL concepts

Developer tooling

CLI tooling

Debugging

Tools

Docker

Podman

Firecracker

VMs

OSWorld

Tau-bench

Job description

Labelbox, the AI data platform, is hiring a Member of Technical Staff to own the design, development, and production of frontier data products. You will build the sandboxed, reproducible environments AI agents rely on during training and evaluation, the terminals, browsers, and tool-augmented workspaces they operate inside.

This is a hands-on engineering role. You’ll write production-quality infrastructure, integrate with the broader RL tooling ecosystem, and partner closely with our data