# Staff ML Engineer, Agent Training & Environments

Hiring organization: [Labelbox](https://career.thegoodapps.co/organizations/labelbox)

Canonical page: https://career.thegoodapps.co/jobs/798522ae-e2c4-425c-b420-2643415fdf1f

Listed on Labelbox's own careers site. Applications go to them directly.

- Employment type: full time
- Seniority: Lead / Staff / Principal
- Location: San Francisco, CA
- Salary: 250000 – 280000 USD per year

## Summary

Build infrastructure and systems that enable frontier AI labs to train and evaluate agentic models, bridging high-throughput platform engineering with deep reinforcement learning expertise. This role combines designing RL environments and reward systems, implementing verification and grading pipelines, and scaling fine-tuning infrastructure for teams pushing the boundaries of AI agents.

_Our summary, not Labelbox's wording._

## Skills named

Apache Kafka, Google Cloud Platform, GraphQL, Java, Kotlin, Kubernetes, MySQL, Node.js, PostgreSQL, Python, PyTorch, React.js, Redux, TensorFlow, TypeScript

## Required

- 3+ years shipping production systems others rely on
- Strong system and API design judgment
- Daily production code shipped with coding agents
- Build infrastructure for team tooling, CI, and harnesses
- Work effectively in ambiguous startup environments
- Deep Python proficiency
- Fine-tuned models for agentic tasks using SFT and at least one RL method
- Built environments for agents to operate in
- Designed verifiers or graders for open-ended work
- Forensic debugging of training runs
- Understand compute economics and experimental efficiency
- Document and communicate learnings to the team

## Nice to have

- Experience with agent harnesses and coding agents in training and evaluation
- Multi-tenancy and sandboxing for untrusted agent execution
- Production distributed systems, ML infrastructure, or data systems at scale
- Direct experience with frontier labs or highly technical customers

Apply on Labelbox's site: https://job-boards.greenhouse.io/labelbox/jobs/5199053007