Research Engineer, Retrieval & Search, Applied Engineering

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

Research Engineer focused on retrieval and search algorithms and methodologies for production deployment in API and ChatGPT, involving novel research and collaboration with cross-functional teams. Requires experience in production ML systems, vector databases, and internet-scale search.

What you'd actually do

  1. Work on retrieval & search algorithms and methodologies in close collaboration with our research team, including problems in such domains as document search, enterprise search, knowledge retrieval, and web-scale search.
  2. Deploy these search methodologies into production in both the API and ChatGPT to be used by millions of end users.
  3. Explore novel research topics in retrieval & search that may inform our product strategy in the medium and long term.
  4. Partner with researchers, engineers, product managers, and designers to bring new features and research capabilities to the world

Skills

Required

  • retrieval & search algorithms
  • production machine learning systems
  • vector databases
  • search indices
  • internet-scale search systems
  • collaboration with research teams
  • deployment into production

Nice to have

  • document search
  • enterprise search
  • knowledge retrieval
  • web-scale search

What the JD emphasized

  • extensive prior experience building and maintaining production machine learning systems
  • prior experience working with vector databases, search indices, or other data stores for search and retrieval use cases
  • prior experience building and iterating on internet-scale search systems
  • Own problems end-to-end
  • move fast in an environment where things are sometimes loosely defined and may have competing priorities or deadlines

Other signals

  • Deploying retrieval & search methodologies into production
  • Exploring novel research topics in retrieval & search
  • Partnering with researchers, engineers, product managers, and designers
  • Building and maintaining production machine learning systems
  • Working with vector databases, search indices, or other data stores for search and retrieval use cases
  • Building and iterating on internet-scale search systems