Waymo
Senior Staff Machine Learning Engineer, Optimization
Waymo, Mountain View, California, us, 94039
Overview
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. Scale is driven by large models and data; we are moving to ever larger models with broader data and to support multiple compute platforms for onboard and offboard simulations. In this role you work embedded in an ML Engineering and Modeling team, collaborating to drive scale and multi-platform support of the models, optimizing neural model inference and training for deployment of larger models and end-to-end systems. You will stay current with the latest developments in efficient ML and bring innovations to Waymo’s production systems. You Will Optimize neural model architectures and systems for high performance across diverse GPU and TPU platforms (onboard and simulation). Enhance neural model and system performance for real-time constrained environments, such as Waymo's onboard systems. Develop and apply post-training and low-level optimizations (e.g., quantization, kernel optimization) to improve inference speed and reduce memory footprint on modern accelerators. Innovate new neural model architectures (e.g., sparse) and decoding strategies (e.g., speculative) to boost inference performance on GPUs and TPUs. Optimize training speed and efficiency for large, memory-bound models and I/O-bound fine-tuning processes. Foster collaboration with ML infrastructure, hardware, simulation, and Alphabet research teams. You Have
Education: Master’s degree or PhD in Computer Science, Engineering, or a related technical field. Experience: 6+ years in software development for neural model inference or training, with 3+ years specifically optimizing these on GPU/TPU architectures. 3+ years developing real-time systems, ideally on-device (e.g., Waymo's onboard). 3+ years in a technical leadership role within large ML Engineering organizations. Technical Skills: Proficient in C++, Python, and modern deep learning toolkits like PyTorch or JAX. Passionate about driving engineering excellence and efficient model development through automation, evaluation and verification of models in production We Prefer
Experience with ML-driven production systems, covering large-scale data, training, evaluation, and deployment. Proficiency in developing and optimizing large-scale vision, video, or multi-modal foundation models. Familiarity with end-to-end model development challenges. Ability to thrive in a fast-paced environment. Details
Hybrid Seniority level
Mid-Senior level Employment type
Full-time Job function
Engineering and Information Technology Industries
Technology, Information and Internet Waymo employees are also eligible to participate in Waymo’s discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range
$281,000—$356,000 USD
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Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. Scale is driven by large models and data; we are moving to ever larger models with broader data and to support multiple compute platforms for onboard and offboard simulations. In this role you work embedded in an ML Engineering and Modeling team, collaborating to drive scale and multi-platform support of the models, optimizing neural model inference and training for deployment of larger models and end-to-end systems. You will stay current with the latest developments in efficient ML and bring innovations to Waymo’s production systems. You Will Optimize neural model architectures and systems for high performance across diverse GPU and TPU platforms (onboard and simulation). Enhance neural model and system performance for real-time constrained environments, such as Waymo's onboard systems. Develop and apply post-training and low-level optimizations (e.g., quantization, kernel optimization) to improve inference speed and reduce memory footprint on modern accelerators. Innovate new neural model architectures (e.g., sparse) and decoding strategies (e.g., speculative) to boost inference performance on GPUs and TPUs. Optimize training speed and efficiency for large, memory-bound models and I/O-bound fine-tuning processes. Foster collaboration with ML infrastructure, hardware, simulation, and Alphabet research teams. You Have
Education: Master’s degree or PhD in Computer Science, Engineering, or a related technical field. Experience: 6+ years in software development for neural model inference or training, with 3+ years specifically optimizing these on GPU/TPU architectures. 3+ years developing real-time systems, ideally on-device (e.g., Waymo's onboard). 3+ years in a technical leadership role within large ML Engineering organizations. Technical Skills: Proficient in C++, Python, and modern deep learning toolkits like PyTorch or JAX. Passionate about driving engineering excellence and efficient model development through automation, evaluation and verification of models in production We Prefer
Experience with ML-driven production systems, covering large-scale data, training, evaluation, and deployment. Proficiency in developing and optimizing large-scale vision, video, or multi-modal foundation models. Familiarity with end-to-end model development challenges. Ability to thrive in a fast-paced environment. Details
Hybrid Seniority level
Mid-Senior level Employment type
Full-time Job function
Engineering and Information Technology Industries
Technology, Information and Internet Waymo employees are also eligible to participate in Waymo’s discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range
$281,000—$356,000 USD
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