About
In this hybrid role you will report to a Technical Lead Manager within the Semantics subgroup in our Perception org.
You will:
Architect and train large-scale, onboard ML perception models that are instrumental to ensuring vehicle safety and regulatory compliance.
Drive cross-functional collaboration to engineer robust, high-reliability training pipelines within a dynamic, rapid-delivery environment.
Leverage deep computer vision expertise to design novel, custom architectures from first principles to solve complex perception challenges.
Contribute to a vibrant and positive team culture where diverse skill sets and backgrounds are valued. Support the growth of junior engineers and foster a high-performing, collaborative team environment.
You have:
Masters in Computer Science or a similar discipline, or an equivalent amount of deep learning experience
3+ years experience in Machine Learning and/or Computer Vision
Experience with Python
Experience with ML frameworks like PyTorch or JAX
We prefer:
Experience in training and deploying ML models on the edge
Experience in Autonomous Vehicle or related industries
PhD Degree in Machine Learning, Robotics, Computer Science or a similar discipline
Publications at top-tier conferences like CVPR, ICCV, ECCV, ICLR, ICML, ICRA, IROS, RSS, NeurIPS, AAAI, IJCV, PAMI
Experience with C++
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 $213,000—$263,000 USD
Languages
- English
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