Labelbox
Forward Deployed Engineer, RL Environments
$140K–$200K
San Francisco Bay Area · Full-time · Posted Apr 7, 2026
- Experience
- 2+ years of professional software engineering experience.
About the job
Design, build, and operate reliable, sandboxed reinforcement learning environments for AI agent training and evaluation.
What you'll do
- Build containerized, reproducible environments and integrate them with agentic tooling and RL workflows.
- Add instrumentation, testing, deployment, and monitoring to ensure environments produce reliable, auditable data.
- Work with data operations on task curricula and evaluation protocols, and prototype new environment types.
What they ask for
- 2+ years of professional software engineering experience; strong Python and at least one of Go, Rust, or C++.
- Production or near-production experience with containerization and sandboxing.
- Familiarity with RL concepts and experience building or maintaining developer tooling, CLI tools, or infrastructure automation.
- Comfort with browser automation or terminal interaction tooling; strong debugging skills.
Nice to have
- Experience with RL environments or agentic AI evaluation frameworks.
- Familiarity with GCP or AWS; prior AI-sector experience or open-source contributions.
Pay
$140,000 — $200,000 USD (base salary)
Tools
Python, Go, Rust, C++, Docker, Podman, Firecracker, Gymnasium/Gym
AI focus
Build and operationalize reinforcement learning environments used to train and evaluate AI agents; the role does not involve ML research.
Model-written summary · the original posting is authoritative