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Software Engineer III, AI/ML, TPU Efficiency, YouTube

Google
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Mountain View, CA, USA$147k - $210kFull-timePosted 2w ago

About the role

Google YouTube software engineer role focused on optimizing ML workloads and TPU/accelerator efficiency for the YouTube recommendations stack, with opportunities to engage across ML models, compilers, and hardware-software co-design.

Responsibilities

  • Analyze ML workloads, identify compute and memory bandwidth bottlenecks, and optimize accelerator utilization to maximize compute efficiency.
  • Explore, implement, and productionize algorithmic efficiency techniques, including low-precision quantization, knowledge distillation, parameter sharing, and attention optimizations.
  • Optimize auxiliary serving and distributed data pipelines, including data ingestion, feature transformation, embedding lookups, and memory caching to support real-time training and inference.
  • Collaborate with ML model developers and researchers to co-design hardware-friendly model architectures and deploy universal efficiency libraries.

Qualifications

  • Bachelor's degree or equivalent practical experience.
  • 2 years of experience with ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging).
  • 2 years of experience with accelerator hardware architectures (TPUs/GPUs).
  • 2 years of experience programming in C++ and Python.
  • Experience with ML frameworks such as TensorFlow, JAX, and PyTorch, or ML compilers (e.g., accelerated linear algebra (XLA)).
  • Experience with ML model optimization.

Skills

Required:ML infrastructureAccelerator hardware (TPUs/GPUs)C++PythonML frameworks (TensorFlow, JAX, PyTorch) or ML compilers (XLA)
Last updated Oct 23, 2026. Interested? Apply on the company site.

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