Research Operations, Discovery

Anthropic Anthropic · AI Frontier · San Francisco, CA · AI Research & Engineering

This role supports a research organization focused on building AI scientist systems. It involves managing operational infrastructure, research partnerships, internal programs, and contributing to science product development. The role requires a blend of operations, TPM, and product strategy, with a focus on building systems and processes from scratch.

What you'd actually do

  1. Build and manage custom expert contractor networks, sourcing domain specialists for eval and training data work that requires expertise beyond standard channels
  2. Run research partnerships with external partners, from scoping through delivery
  3. Provide end-to-end TPM support for major research pushes—coordinating across teams, dependencies, and keeping stakeholders aligned
  4. Ensure that our research progress is complemented by products that enable scientists to make maximal use of model capabilities.
  5. Partner with product teams to contribute to science product strategy, product design, and novel product integrations where research and product intersect

Skills

Required

  • experience in research operations, technical program management, or a related role
  • context-switch fluidly between operational work and higher-order work
  • technical background, with experience in software development, machine learning, or biology R&D
  • comfortable working directly with research scientists and engineers
  • track record of building systems and processes from scratch
  • strong written communication skills
  • managed contractors or external partners before
  • results-oriented, with a bias toward flexibility and impact
  • thrive in ambiguous, fast-moving environments

Nice to have

  • Direct experience sourcing and managing expert contractor networks, particularly in technical or scientific domains
  • Familiarity with ML research workflows—training runs, evaluations, data pipelines—and what makes them succeed or stall
  • Experience contributing to product development or product strategy

What the JD emphasized

  • building systems and processes from scratch
  • technical background
  • ML research workflows