AI Engineer, RL
Build evaluation methods, RL environments, agent tooling, and scalable infrastructure that make subjective qualities such as design and taste measurable for frontier AI models. The role requires experience with evaluations, RL environments, ML or post-training, plus strong backend engineering skills.
About the job
Responsibilities
- Research grading methods and rubrics for subjective domains such as design and taste.
- Design tasks that capture elements of taste and design capabilities.
- Build agent harnesses and context layers.
- Work on scalable reinforcement-learning infrastructure.
- Collaborate with internal research teams on training pipelines.
- Partner with frontier labs to craft environments that improve frontier models.
Requirements
- Experience building evaluations, reinforcement-learning environments, machine learning systems, or post-training workflows.
- Strong backend engineering experience.
- Ability to work on ambiguous, difficult, and creative problems.
- Ownership-oriented, adaptable, collaborative approach in a fast-moving startup environment.
Nice-to-haves
- Open-source contributions or personal projects demonstrating curiosity and initiative.
- Background at creative companies such as Figma, Notion, Canva, Adobe, or Runway.
- Experience at companies focused on indexing, crawling, or data, such as Firecrawl, Brave, Luma, Pika, Mercor, or Surge.
Skills
Reinforcement Learning, Machine Learning, Post-Training, Backend Engineering, Rl Infrastructure, Machine Learning Evaluations, Rl Environments, Agent Harnesses, Context Layers, Training Pipelines, Open Source, Indexing
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