Staff ML Engineer, Perception, Computer Vision

Remote, USA Full-time
Waymo is an autonomous driving technology company with the mission to be the worlds most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The Worlds 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. Our Perception team builds the system that sees the world around the self-driving car. We conduct research to address real-world problems and collaborate with research teams at Alphabet. We have access to millions of miles of driving data from a diverse set of sensors, enabling researchers like you to develop complex models and techniques at scale. In this hybrid role, you will report to a Technical Lead Manager. You will:• Drive the research, design, and implementation of state-of-the-art computer vision and deep learning models for autonomous driving, with a focus on semantic understanding.• Lead the development of novel computer vision algorithms to solve critical real-world perception problems in a safety-critical production environment. • Push the boundaries of computer vision model performance, efficiency, and robustness across diverse operating conditions. • Collaborate with ML infrastructure and Onboard teams to deploy and optimize models on in-vehicle hardware with real-time constraints. • Mentor junior engineers and contribute to the technical vision and roadmap for the Perception teams CV stack.• Stay current with the latest academic and industry research in Computer Vision and Machine Learning and apply relevant findings. You have:• Master’s degree or PhD in Computer Science, Engineering, or a related technical field with a specialization in Computer Vision or Machine Learning. • 5+ years of experience in developing and deploying computer vision models in a professional or research setting. • Demonstrated expertise in deep learning frameworks such as PyTorch or TensorFlow/JAX, and strong proficiency in Python and C++.• Proven ability to lead complex technical projects and drive research ideas from conception to production deployment. • Deep understanding of modern computer vision architectures and their practical application. • Experience with large-scale data, model training, and evaluation pipelines for computer vision tasks. • Strong communication and collaboration skills in a fast-paced, cross-functional environment. We prefer:• Experience in the autonomous vehicle (AV) or robotics industry, particularly with real-time on-device perception systems.• Proven track record of publications at top-tier computer vision or machine learning conferences (e.g., CVPR, ICCV, ECCV, NeurIPS). • Experience with Multi-Modal Large Language Models (MLLMs), diffusion models, and advanced reasoning techniques. • Experience with model optimization techniques such as quantization, pruning, or knowledge distillation. • Familiarity with distributed training and inference optimization on GPU/TPU clusters. The expected base salary range for this full-time position across US locations is listed below.Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. 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$238,000—$302,000 USD Apply tot his job
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