Research Platform Engineer

World Labs World Labs · AI Frontier · San Francisco, CA · Research

World Labs is seeking a Research Platform Engineer to build and maintain the critical systems supporting their AI research. This senior role involves designing, developing, and shipping code for training and data infrastructure, productionizing models for serving, optimizing inference, and enhancing research velocity and developer experience. The ideal candidate has strong distributed systems foundations, performance optimization skills, and experience working with ML researchers.

What you'd actually do

  1. Design and build training infrastructure, data infrastructure, and data processing and sourcing pipelines.
  2. Productionize models for serving and own parts of the inference stack.
  3. Build internal tools and services that increase engineering and research velocity.
  4. Debug hard problems across training, inference, and performance — including distributed systems issues under real research workloads.
  5. Optimize throughput, latency, GPU utilization, and system-level scaling.

Skills

Required

  • Python
  • Distributed systems
  • Performance optimization
  • ML infrastructure
  • Production systems
  • Infrastructure ownership

Nice to have

  • C++
  • CUDA
  • Rust
  • Go
  • Large-scale training systems
  • High-throughput inference
  • Low-level performance optimization
  • Developer experience tooling

What the JD emphasized

  • 5+ years of experience building and shipping production systems, with demonstrated ownership of infrastructure used by other engineers or researchers.
  • Strong depth in at least one of: ML infrastructure, distributed training or inference systems, data systems, or research tooling.
  • Strong distributed systems foundations
  • Strong performance optimization skills
  • Strong proficiency in Python, with the ability to work in C++, CUDA, Rust, or Go as the work demands.
  • Experience working directly with ML researchers or research engineers, including productionizing research code.
  • A product engineer's instincts for iteration speed and developer experience
  • High-ownership mindset

Other signals

  • building mission-critical systems for research
  • productionizing models for serving
  • optimizing inference performance
  • improving research iteration speed