Research Engineer / Research Scientist / AI Systems Engineer, Rsi

OpenAI OpenAI · AI Frontier · San Francisco, CA · Research

The Recursive Self-Improvement (RSI) team at OpenAI is building AI systems to accelerate and conduct high-quality research. This role involves designing evaluations, turning research workflows into data flywheels, improving model research capabilities through agent harnesses and synthetic data, building safe integrations with research infrastructure, and developing research agents and experiment-orchestration systems. The role requires a strong generalist comfortable with ambiguity, moving between research and implementation, and building data pipelines and tooling.

What you'd actually do

  1. Design evaluations for research judgment, hypothesis generation and testing, and long-horizon experiment execution.
  2. Turn real research workflows and model failures into data and evaluation flywheels.
  3. Improve model research capabilities through agent harnesses, synthetic data, RL environments, and model training.
  4. Build and maintain safe, reliable integrations between our models and OpenAI’s research infrastructure.
  5. Develop research agents, experiment-orchestration systems, and sandboxed runtimes that support real research workflows.

Skills

Required

  • LLM training
  • model evaluations
  • agent systems
  • synthetic data
  • research infrastructure
  • large-scale distributed systems
  • generalist
  • open-ended research
  • practical implementation
  • systems
  • data
  • model training
  • evaluations
  • data pipelines
  • tooling
  • infrastructure

Nice to have

  • RL environments

What the JD emphasized

  • high-quality research
  • automating research
  • research workflows
  • model failures
  • model research capabilities
  • research infrastructure
  • research agents
  • experiment-orchestration systems
  • researchers
  • research
  • research infrastructure
  • research teams
  • emerging AI capabilities
  • scientific quality
  • research taste
  • research productivity
  • meaningful research

Other signals

  • Automate research workflows
  • Improve research productivity
  • Build systems and feedback loops
  • Design evaluations
  • Train models to develop missing capabilities