Staff ML Engineer, Generative Model Performance & Efficiency
Mountain View, California$251k - $310kFull-timePosted 3mo ago
About the role
Staff ML Engineer role focusing on performance and efficiency of generative models within Waymo's Simulator Team, applying advanced ML techniques to optimize training/inference, design low-latency serving, and build profiling/tools.
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.
Qualifications
- 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.
Skills
Required:Transformer architecturesDiffusion ModelsMixture of Experts (MoEs)QuantizationPruningKnowledge DistillationProfiling and DebuggingPython
Nice to have:C++
Benefits
- Discretionary annual bonus program
- Equity incentive plan
- Generous Company benefits program
Last updated Oct 22, 2026. Interested? Apply on the company site.
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