Waymo
Senior Machine Learning Engineer, Perception, Semantics
Waymo, Mountain View, California, us, 94039
Senior Machine Learning Engineer, Perception, Semantics
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. 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.
Within the Perception organization, the Semantics core team includes subgroups focusing on Vulnerable Road Users (VRUs), Traffic Control, and Scene Semantics, addressing pedestrians/cyclists, traffic controls and map robustness, and unstructured environments respectively. These teams collaborate to build robust perception systems for safe autonomous operation.
In this hybrid role, you will report to the Technical Lead Manager of Semantics.
You Will
Develop state-of-the-art ML models to understand complex and dynamic scenes, enabling vehicles to navigate varied traffic controls, pedestrian and cyclist interactions, construction zones, emergency scenes, and/or mapless driving.
Own the end-to-end ML pipeline, from data mining and labeling to training and deployment of models.
You Have
4+ years of experience in Machine Learning, with a strong focus on computer vision and/or deep learning for perception tasks.
Deep understanding of state-of-the-art ML techniques for object classification, detection, tracking, pose estimation, and/or action recognition.
Proficiency in at least one major deep learning framework (e.g., TensorFlow, PyTorch, JAX).
We Prefer
PhD degree in Computer Science or a similar discipline, or an equivalent amount of deep learning experience.
Experience with multi-modal perception systems (e.g., combining camera, lidar, radar data).
Familiarity with foundation models and techniques for model adaptation (e.g., few-shot learning, transfer learning, domain adaptation).
Experience in optimizing ML models for on-device deployment and real-time performance.
Background in autonomous driving, robotics, or a related safety-critical domain.
Publications in top-tier ML/CV conferences (e.g., NeurIPS, ICML, CVPR, ICCV, ECCV).
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
$204,000—$259,000 USD
Seniorities and Employment
Seniority level: Mid-Senior level
Employment type: Full-time
Job function: Engineering and Information Technology
Industries: Technology, Information and Internet
Referrals increase your chances of interviewing at Waymo. Get notified about new Machine Learning Engineer jobs in Mountain View, CA.
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Within the Perception organization, the Semantics core team includes subgroups focusing on Vulnerable Road Users (VRUs), Traffic Control, and Scene Semantics, addressing pedestrians/cyclists, traffic controls and map robustness, and unstructured environments respectively. These teams collaborate to build robust perception systems for safe autonomous operation.
In this hybrid role, you will report to the Technical Lead Manager of Semantics.
You Will
Develop state-of-the-art ML models to understand complex and dynamic scenes, enabling vehicles to navigate varied traffic controls, pedestrian and cyclist interactions, construction zones, emergency scenes, and/or mapless driving.
Own the end-to-end ML pipeline, from data mining and labeling to training and deployment of models.
You Have
4+ years of experience in Machine Learning, with a strong focus on computer vision and/or deep learning for perception tasks.
Deep understanding of state-of-the-art ML techniques for object classification, detection, tracking, pose estimation, and/or action recognition.
Proficiency in at least one major deep learning framework (e.g., TensorFlow, PyTorch, JAX).
We Prefer
PhD degree in Computer Science or a similar discipline, or an equivalent amount of deep learning experience.
Experience with multi-modal perception systems (e.g., combining camera, lidar, radar data).
Familiarity with foundation models and techniques for model adaptation (e.g., few-shot learning, transfer learning, domain adaptation).
Experience in optimizing ML models for on-device deployment and real-time performance.
Background in autonomous driving, robotics, or a related safety-critical domain.
Publications in top-tier ML/CV conferences (e.g., NeurIPS, ICML, CVPR, ICCV, ECCV).
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
$204,000—$259,000 USD
Seniorities and Employment
Seniority level: Mid-Senior level
Employment type: Full-time
Job function: Engineering and Information Technology
Industries: Technology, Information and Internet
Referrals increase your chances of interviewing at Waymo. Get notified about new Machine Learning Engineer jobs in Mountain View, CA.
#J-18808-Ljbffr