Forward Deployed Engineer, RL Environments
Core
Design, build, and maintain sandboxed reinforcement learning environments for agentic AI training and evaluation, including terminal emulators, browser automation harnesses, and computer-use simulators.
Role type
Senior IC software engineer (RL infrastructure)
Builds
Sandbox execution environments, containerized task rollouts, and observability layers for AI agents
Domain
Artificial Intelligence / Reinforcement Learning Infrastructure
Deliverable
production ML models
Required skills
Python, systems-level languages (Go, Rust, C++), containerization (Docker, Podman, Firecracker), RL concepts (MDPs, reward shaping), CLI/API development, debugging across process boundaries, reading academic papers
Preferred skills
RL environment frameworks (Gymnasium, PettingZoo), agentic evaluation frameworks (SWE-bench, WebArena, OSWorld), cloud infrastructure (GCP, AWS), open-source contributions
Technologies
Docker, Podman, Firecracker, TerminalBench, OSWorld, Tau-bench, GCP, AWS
Responsibilities
Design and build sandboxed RL environments for agentic AI training; Develop reproducible, containerized execution environments; Integrate with open-source agentic tooling and custom CLI/API harnesses; Build instrumentation and observability layers for training runs; Collaborate on task curricula and evaluation protocols; Own environment deployment, CI/CD pipelines, and automated testing
Seniority
Senior, hands-on IC
