Anthropic Fellows Program — ML Systems & Performance

Anthropic Anthropic · AI Frontier · BC +3 · Remote · AI Research & Engineering

This is a research fellowship program focused on AI systems and performance, with the goal of producing public outputs like paper submissions. Fellows will work on empirical projects, potentially involving building ML systems, data pipelines, or infrastructure for accelerators, using external infrastructure and open-source models.

What you'd actually do

  1. Work on an empirical project aligned with our research priorities, with the goal of producing a public output (e.g. a paper submission).
  2. Building a CPU simulator for accelerator workloads
  3. Adding backends for different accelerators on an open source project
  4. Building on demand infrastructure for other infrastructure heavy fellows projects
  5. Building complex synthetic data or environment pipelines

Skills

Required

  • Fluent in Python programming
  • Available to work full-time on the Fellows program

Nice to have

  • Strong technical background in computer science, mathematics, or physics
  • Strong software engineering skills with experience building complex ML systems
  • Can balance research exploration with engineering rigor and operational reliability
  • Enjoy collaborating across research and engineering disciplines
  • Are comfortable working with large-scale distributed system

What the JD emphasized

  • public output
  • paper submission
  • CPU simulator
  • accelerator workloads
  • backends for different accelerators
  • on demand infrastructure
  • synthetic data
  • environment pipelines
  • ML systems
  • engineering rigor
  • operational reliability
  • large-scale distributed system

Other signals

  • AI safety
  • AI systems
  • ML systems
  • performance
  • empirical project
  • public output
  • paper submission