Staff ML Engineer, Generative Model Performance & Efficiency

Responsibilities

• Analyze model architectures and identify bottlenecks in training and inference performance (e.g., memory bandwidth, compute, communication).
• Apply and develop techniques such as quantization (e.g., FP8, INT4), pruning, knowledge distillation, and efficient attention mechanisms.
• Optimize model code for specific hardware accelerators (TPUs, GPUs), leveraging compiler features and low-level libraries (e.g., XLA).
• Experiment with different model partitioning and sharding strategies (e.g., data, tensor, pipeline parallelism, expert parallelism) to improve scalability and efficiency.
• Design and implement low-latency, high-throughput serving solutions for generative models and optimize training pipelines to reduce training time.
• Build and maintain tools for performance analysis, profiling (e.g., xprof), and debugging of ML models.

Requirements

• MS or PhD in Computer Science, Machine Learning, Robotics, or a related field.
• 5+ years of experience with deep learning architectures (especially Transformers, Diffusion Models, MoEs), algorithms, and optimization techniques.
• Proficiency in JAX, Flax, and potentially TensorFlow/PyTorch.
• Expertise in using profiling tools (e.g., XProf, Perfetto, NVIDIA Nsight) to diagnose performance issues in ML workloads.
• Hands-on experience with quantization, pruning, distillation, and other model compression methods.
• Strong programming skills in Python and potentially C++, with experience in software development best practices.

Preferred

• Knowledge of TPU and GPU architectures and how to optimize code for them.
• Familiarity with ML compilers like XLA and an understanding of how they translate high-level code to efficient hardware instructions.
• Understanding of concepts related to training and serving models across multiple devices and machines.
• Experience contributing to frameworks and libraries that improve training speed and scalability (e.g., JAX, Gemax, XManager).

Qualifications

Waymo is an equal employment opportunity employer. We are committed to providing equal employment opportunities for all applicants and employees. We do not engage in or tolerate discrimination on the basis of race, color, gender, national origin, sexual orientation, gender identity or expression, age, disability, veteran status, pregnancy, marital status, or any other protected status. We will consider for employment qualified applicants with criminal histories consistent with applicable law.