Senior Machine Learning Engineer, Vehicle Perception
Product & Technology - AD/ADAS
Palo Alto, CA
hybrid
TEAM
WHO ARE WE LOOKING FOR?
RESPONSIBILITIES
- Senior Lead the design and development of perception foundation models for autonomous vehicles, unifying diverse sensor data for scalable 3D scene understanding.
- Deploy scalable and efficient ML models on our autonomous vehicle platform.
- Integrate modern technologies with rigorous safety standards while maintaining cost efficiency.
- Significantly contribute to development of needed components for end-to-end ML training and deployment, from data strategy to optimization and validation.
- Be a champion of the scientific method and critical thinking in inventing state-of-the-art deep learning solutions
- Work in a high-velocity environment and employ agile development practices.
- Collaborate closely with teams such as Perception, Motion Planning, Simulation, Infrastructure, and Tooling to drive unified solutions.
- Work in a hybrid workspace, with the requirement to be present in our Nihonbashi (Japan), Palo Alto (California), or Ann Arbor (Michigan) offices three days per week.
MINIMUM QUALIFICATIONS
-
MS or PhD in Machine Learning, Computer Vision, Robotics or related quantitative fields, or equivalent industry experience.
-
3+ years of experience with Python, any major deep learning framework (PyTorch preferred), and software engineering best practices
-
3+ years of experience with deep learning approaches such as supervised/unsupervised learning, transfer learning, multi-task learning, and/or deep reinforcement learning.
-
3+ years of experience covering machine learning workflows, data sampling and curation, pre-processing, model training, ablation studies, evaluation, deployment, and inference optimization.
-
Experience working with large-scale foundation models, including pretraining, multimodal architectures, self-supervised learning approaches.
-
Deep understanding of runtime complexity, distributed/cloud ML infrastructure, data pipeline architecture,resource-aware optimization.
-
Comfortable in writing C++ code to help integrate with our autonomous vehicle platform.
-
Strong leadership skills to influence others and the team's technical strategy.
-
Strong communication skills with the ability to communicate concepts clearly and precisely.
NICE TO HAVES
-
Published research at top-tier conferences (NeurIPs, CVPR and similar).
-
Proven track record of deploying ML models at scale in self-driving or related fields.
-
Experience with offboard, auto-labeling, or "data-engine" pipelines, including mining, curation, active learning, and ground-truth-free evaluation for large-scale datasets.
-
Hands-on experience with vision-language models (VLMs), world models, video prediction, or latent dynamics models for autonomous systems or robotics.
-
Experience leveraging foundation models across multiple platforms and sensor setups, including distilling larger models into efficient real-time variants.
-
Familiarity with production-level coding and deployment onto embedded platforms, optimizing for latency and hardware constraints.
-
Experience in self-driving challenges (Perception, Prediction, Mapping, Localization, Planning, Simulation).
Your base salary is one part of your total compensation. We offer a base salary, short term and long term incentives, and a comprehensive benefits package. The total compensation offered to an employee will be dependent upon the individual's skills, experience, qualifications, location, and level.