Senior Machine Learning Engineer

RESPONSIBILITIES

• (Senior) Lead the design and development of perception foundation models for autonomous vehicles, unifying diverse sensor data for scalable 3D scene understanding
• (Non-Senior) Design and develop advanced machine learning perception models specifically tailored for autonomous vehicles utilizing deep learning and large-scale data analysis
• 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, 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 pre training, 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
• Hands-on experience with 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)