ML Systems Engineer: TPU Efficiency & Optimization

Google LLC; Mountain View (CA); On-site; USD 147,000 - 210,000; Full time

Job summary

Google's YouTube team in Mountain View seeks a Software Engineer III, ML to optimize TPU-based model efficiency. You will focus on reducing training and serving costs through techniques like low-precision quantization, knowledge distillation, and hardware-friendly model design.

You'll build and optimize models in the Recommendation System stack and collaborate across ML and hardware teams to scale TPU workloads and improve overall pipeline performance.

Qualifications

• Bachelor's degree or equivalent practical experience.
• 2 years of experience programming in C++ or Python.
• 2 years of experience with software design and architecture.
• 2 years of experience testing, and launching software products.
• Experience with ML model optimization.
• Experience with ML frameworks such as TensorFlow, JAX, and PyTorch, or ML compilers (e.g., XLA).

Responsibilities

• Profile ML workloads and optimize accelerator utilization.
• Explore and productionize efficiency techniques like quantization and distillation.
• Collaborate with ML model developers and hardware teams to design efficient architectures.
• Support real-time training and inference in the YouTube Recommendation stack.

Skills

C++/Python programming

Software design

Testing & deployment

ML optimization

ML frameworks

Education

Bachelor's degree or equivalent

Master's degree or PhD in Computer Science

Tools

XLA

TPU/GPUs familiarity

Job description

Google's YouTube team in Mountain View seeks a Software Engineer III, ML to optimize TPU-based model efficiency. You will focus on reducing training and serving costs through techniques like low-precision quantization, knowledge distillation, and hardware-friendly model design.

You'll build and optimize models in the Recommendation System stack and collaborate across ML and hardware teams to scale TPU workloads and improve overall pipeline performance.