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Staff ML Engineer, Agent Training & Environments
Labelbox
San Francisco, California, United States
Full Time
Hybrid
Senior
USD 250,000 – 280,000
Technology
Information Technology Telecommunications
Posted 3 days ago
Job summary
The role involves building and running the systems for training agents in reinforcement learning environments, including experiment pipelines, verifiers, and evaluation infrastructure, focusing on reliability, scaling, and efficiency.
Responsibilities
You will build and maintain the infrastructure, environments, and evaluation systems used to train and test frontier AI agents. This involves developing verifiers, managing fine-tuning pipelines, and scaling training infrastructure to support high-throughput experimentation.
Qualifications
API Design
Distributed Systems
Evaluation Pipelines
Fine-tuning Models
ML Infrastructure
Open-ended Work Verifiers or Graders
Python
Reinforcement Learning
RL Algorithms (e.g., PPO, GRPO)
System Design
The role requires over 3 years of experience shipping reliable production systems and deep expertise in post-training reinforcement learning methods. Candidates must demonstrate strong system design judgment and the ability to work effectively in a fast-paced, startup-style environment.
English
Company
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Staff ML Engineer, Agent Training & Environments
Company
Labelbox
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