Staff ML Engineer - Simulation & Efficient Inference

Waymo; United States; On-site; USD 251,000 - 310,000; Full time

Job summary

Waymo is seeking a seasoned ML systems engineer to advance the Waymo Driver’s AI stack. You will analyze architectures, reduce training and inference bottlenecks, and implement efficient techniques like quantization and distillation.

The role emphasizes cross‑device optimization on TPUs/GPUs and scalable data/model parallelism. The ideal candidate holds a MS/PhD in a relevant field with 5+ years of deep learning experience, strong Python and C++ skills, and hands-on work with JAX, Flax, and ML

Qualifications

• MS or PhD in Computer Science, Machine Learning, Robotics, or related field.
• 5+ years of experience with deep learning architectures, optimization techniques, and ML systems.
• Proficiency in Python; C++ a plus; experience with ML frameworks.

Responsibilities

• Analyze model architectures and identify bottlenecks in training and inference performance.
• Apply and develop techniques such as quantization, pruning, distillation, and efficient attention mechanisms.
• Optimize model code for hardware accelerators (TPUs, GPUs) using compiler features and low-level libraries (XLA).
• Experiment with model partitioning and sharding strategies to improve scalability and efficiency.
• Design and implement low-latency serving solutions and optimize training pipelines to reduce time.
• Build and maintain tools for performance analysis, profiling, and debugging of ML models.

Skills

Transformers MoEs

Diffusion Models

Profiling tools

Python

C++

XLA

ML optimization

Education

MS or PhD in CS/ML/Robotics

Tools

JAX

Flax

TensorFlow/PyTorch

Job description

Waymo is seeking a seasoned ML systems engineer to advance the Waymo Driver’s AI stack. You will analyze architectures, reduce training and inference bottlenecks, and implement efficient techniques like quantization and distillation.

The role emphasizes cross‑device optimization on TPUs/GPUs and scalable data/model parallelism. The ideal candidate holds a MS/PhD in a relevant field with 5+ years of deep learning experience, strong Python and C++ skills, and hands-on work with JAX, Flax, and ML