Member of Technical Staff
$140k - $200k • Remote • San Francisco Bay Area
Posted 25d ago
Job Location
San Francisco Bay Area
Tech Stack
Remote Work Policy
Fully remote
Categories
AI Agent Engineer
About the job
Labelbox is seeking a Member of Technical Staff to lead the design, development, and production of Frontier Data Products. This role involves building the essential sandboxed, reproducible environments that AI agents require for training and evaluation, including terminals, browsers, and tool-augmented workspaces. You will be responsible for writing production-quality infrastructure, integrating with the RL tooling ecosystem, and ensuring environments are robust and observable. A strong understanding of how RL training loops consume environments and potential failure points is crucial.
Responsibilities
- Design, build, and maintain sandboxed RL environments for agentic AI training, including terminal emulators, browser automation harnesses, and tool-augmented workspaces.
- Develop reproducible, containerized execution environments (Docker, VMs, lightweight sandboxes) for deterministic task rollouts and reward signal collection.
- Integrate with and extend open-source agentic tooling and custom CLI/API harnesses for multi-step agent interaction.
- Build instrumentation and observability layers for clean, auditable data from training runs and human annotation sessions.
- Collaborate with data operations to design task curricula and evaluation protocols.
- Own environment deployment and reliability, including CI/CD pipelines, automated testing, and monitoring.
- Rapidly prototype new environment types based on evolving requirements.
Requirements
- 2+ years of professional software engineering experience.
- Strong fundamentals in Python and at least one systems-level language (Go, Rust, C++).
- Demonstrated experience with containerization and sandboxing (Docker, Podman, Firecracker, or similar) in production or near-production contexts.
- Familiarity with RL concepts (MDPs, reward shaping, episode structure, observation/action spaces).
- Experience building or maintaining developer tooling, CLI tools, or infrastructure automation.
- Comfort working with browser automation frameworks or terminal interaction tooling.
- Strong debugging skills across process boundaries, container layers, and network calls.
- Ability to implement from academic papers and open-source benchmark repositories.