or apply directly on Labelbox's site. We never take the application ourselves.
Is this posting real?
- This role has been open
- 31 days Labelbox's roles stay open a median of 82 days
- Reposted
- No
- Salary listed
- No 0% of Labelbox's roles list one
- Ghost-job risk at Labelbox
- high 10 stale, 0 reposted of 11 open
- Hiring momentum
- 11 roles opened in the last 90 days ↑ up vs. the prior 90 days
- Last confirmed on the employer's board
- 2026-10-24
Measured from postings appearing on and disappearing from Labelbox's own greenhouse board since 2026-08-03. Full hiring picture for Labelbox.
About this role
As a Member of Technical Staff at Labelbox, you will design, develop, and maintain sandboxed environments for reinforcement learning (RL) training. This hands-on engineering role involves writing production-quality infrastructure, integrating with existing tools, and collaborating with data operations to ensure robust environments for AI agents. You will also be responsible for deploying environments, monitoring their reliability, and rapidly prototyping new solutions as requirements evolve.
- benefits
- 1/5
- freshness
- 5/5
- career value
- 5/5
- role clarity
- 5/5
- pay transparency
- 0/5
Scored from the posting itself — how clearly the role is described, how much it says about pay and benefits, and how recently it was listed. Not a judgement of Labelbox as an employer.
What you need
- 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)
- 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
Nice to have
- Direct experience building or contributing to RL environments (Gymnasium/Gym, PettingZoo, or custom environment implementations)
- Experience with agentic AI evaluation frameworks (SWE-bench, WebArena, OSWorld, TerminalBench, or similar)
- Familiarity with GCP or AWS infrastructure (Compute Engine, ECS/EKS, Cloud Build)
- Prior work at an AI data company, ML platform company, or AI research lab
- Contributions to open-source projects in the RL, agents, or dev-tools space
What you get
- Annual base salary range of $140,000 — $200,000 USD
- Career advancement opportunities directly tied to your impact
Worth weighing
- No specific mention of remote work options
- Fast-paced and high-intensity environment may not suit everyone
- Role requires a strong grasp of reinforcement learning concepts, which may be challenging for those without prior experience in the field
Summarised from Labelbox's posting. Read the full original.
Listed by Labelbox on their greenhouse job board, last confirmed open on 2026-10-24. PitchMeAI is not the employer.
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