Senior Software Engineer, ML Compilers, Tpu, Youtube

Google Google · Big Tech · San Bruno, CA +2

Senior Software Engineer focused on optimizing ML models for YouTube's RecSys stack by working on ML compilers (XLA, Pallas kernels) for TPUs, including co-design with hardware. This role bridges the gap between ML models and the underlying hardware infrastructure for inference optimization.

What you'd actually do

  1. Contribute to the compiler for a novel processor designed to accelerate machine learning workloads.
  2. Target and compile high-performance implementations of operations at distributed scale.
  3. Design and implement new compiler passes that extract more performance out of current and next-generation TPUs for our unique LEM (Large Embedding Models) requirements, directly impacting fleet efficiency.
  4. Collaborate closely with YouTube’s Next Platform Evaluation team and Google’s hardware designers to co-design future processors.

Skills

Required

  • C++ or Python
  • software design and architecture
  • state-of-the-art ML compilers and their internals
  • writing compiler optimization passes
  • ML frameworks (TensorFlow, JAX, PyTorch) or ML compilers (XLA)

Nice to have

  • Master's degree or PhD in computer science or related technical fields
  • debugging correctness and performance issues at all levels of the ML software stack
  • accelerator HW architectures (TPUs/GPUs)

What the JD emphasized

  • state-of-the-art ML compilers and their internals
  • experience writing compiler optimization passes
  • ML frameworks such as TensorFlow, JAX, and PyTorch, or ML compilers (e.g., accelerated linear algebra (XLA))

Other signals

  • ML Compilers
  • TPU
  • YouTube algorithm optimization
  • XLA
  • Pallas kernels
  • RecSys stack
  • next-generation TPU hardware
  • model and TPU compiler co-design