Forward Deployed Engineer, RL Environments

About this role

Labelbox is seeking a Forward Deployed Engineer to design and build sandboxed reinforcement learning environments where AI agents train and evaluate. You'll develop production infrastructure for terminal-based tasks, browser automation, and computer-use simulators, working closely with data operations to ensure robustness and observability.

What you'll do

• Design and maintain sandboxed RL environments for agentic AI training including terminal emulators, browser automation, and computer-use simulators
• Develop reproducible, containerized execution environments with deterministic task rollouts and reward signal collection
• Build instrumentation and observability layers for trajectory capture, logging, and state snapshotting
• Integrate with open-source agentic tooling and custom CLI/API harnesses for multi-step agent interaction
• Own environment deployment reliability including CI/CD pipelines, automated testing, and version monitoring
• Rapidly prototype new environment types as requirements evolve

What they're looking for

• Python and systems languages (Go, Rust, C++)
• Containerization and sandboxing (Docker, Podman, Firecracker)
• Reinforcement learning concepts (MDPs, reward shaping, observation/action spaces)
• Developer tooling and infrastructure automation
• Browser automation and terminal interaction frameworks
• Debugging across process boundaries and container layers
• Reading and implementing from academic papers and open-source repositories

Benefits

• Work at the cutting edge of AI development with industry leaders
• High-impact environment with expanded responsibilities and rapid career growth
• Clear ownership and autonomy with explicit metrics
• Fast-paced startup culture rewarding high agency and execution
• Continuous learning surrounded by experts solving frontier AI problems