Staff Software Engineer, ML Frameworks

Google Google · Big Tech · Mountain View, CA +1

Staff Software Engineer focused on building and optimizing ML infrastructure, including training and inference software stacks, to support internal and Cloud developers. The role involves innovating infrastructure directions, driving technical strategy, and migrating existing ML frameworks onto a unified ML Runtime.

What you'd actually do

  1. Innovate next directions for infrastructure over a 12-month time horizon, given a rapidly changing technology landscape.
  2. Drive technical strategy and roadmaps for infrastructure development.
  3. Identify and build stable, standardized Application Programming Interfaces (APIs) for internal products.
  4. Migrate existing frameworks (e.g., TensorFlow, JAX, PyTorch), runtimes (TFExecutor, TFRT, PJRT), and Product Area’s custom workflows (AdBrain) onto ML Runtime, minimizing any user disruption.
  5. Partner with Global Delivery Model (GDM) to transfer key innovations into products developed by your team and partner teams.

Skills

Required

  • software development
  • software products
  • software design and architecture
  • Speech/audio
  • reinforcement learning
  • ML infrastructure
  • ML field specialization
  • ML design
  • ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning)

Nice to have

  • data structures and algorithms
  • technical leadership role
  • complex, matrixed organization
  • ML compilers and runtimes
  • Tensor Processing Units (TPUs)
  • TPU system design
  • Graphics Processing Units (GPUs)

What the JD emphasized

  • ML infrastructure
  • training and inference
  • ML design and ML infrastructure

Other signals

  • ML infrastructure
  • training and inference
  • software stacks
  • ML Runtime
  • TensorFlow, JAX, PyTorch