Description
Shape the Future of AI
At Labelbox, we're building critical infrastructure for breakthrough AI models at leading research labs and enterprises. Since 2018, we've pioneered data-centric approaches fundamental to AI development.
The Role
We're hiring a Member of Technical Staff to design, develop, and produce Frontier Data Products. You'll build sandboxed, reproducible environments AI agents rely on during training and evaluation.
What You'll Do
- Design, build, and maintain sandboxed RL environments for agentic AI training
- Develop reproducible, containerized execution environments
- Integrate with and extend open-source agentic tooling and custom CLI/API harnesses
- Build instrumentation and observability layers
- Collaborate with data operations to design task curricula and evaluation protocols
- Own environment deployment and reliability
- Rapidly prototype new environment types
What We're Looking For
- 2+ years of professional software engineering experience with strong fundamentals in Python and at least one systems-level language
- Demonstrated experience with containerization and sandboxing
- Familiarity with RL concepts
- Experience building or maintaining developer tooling, CLI tools, or infrastructure automation
- Comfort working with browser automation frameworks or terminal interaction tooling
- Strong debugging instincts
- Ability to read and implement from academic papers and open-source benchmark repositories
Why This Role Matters
- Reinforcement learning has become the state-of-the-art approach for training agentic AI, and environment quality is one of its biggest bottlenecks
- You'll work across a portfolio of projects spanning different AI labs and model capabilities
- Alignerr is a small, high-impact team inside Labelbox with startup-level ownership and growth-stage resources
Life at Labelbox
- Fast-paced and high-intensity environment
- Career advancement opportunities directly tied to your impact
- Be part of building the foundation for humanity's most transformative technology
This listing is enriched and indexed by YubHub. To apply, use the employer's original posting:
https://job-boards.greenhouse.io/labelbox/jobs/5246362007