Staff Machine Learning Engineer, Behavior

RESPONSIBILITIES

• Define the technical roadmap for the team towards short and long term development. 
• Initiate and Influence cross-functional teams towards common development goals.
• Initiate high risk, high rewards projects towards overall business goals. 
• Guide the design and development towards advanced machine learning models in the behavior space 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.
• Own development of new ML models end-to-end from data strategy, initial development, optimization, production platform validation, and fine tuning based on metrics and on road performance.
• Lead large, multi-person projects and significantly influence the overall Motion Planning architecture and technical direction.
• Enable and help other engineers on the team to be more effective through coaching and leading by example and by providing high-quality code and design document reviews and delivering rigorous reports from ML experiments.
• 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 to invent 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, Simulation, Infrastructure, and Tooling to drive unified solutions.

MINIMUM QUALIFICATIONS

• MS or PhD in Machine Learning, Computer Science, Robotics or related quantitative fields, or equivalent industry experience.
• 5+ years of experience with Python, any major deep learning framework, and software engineering best practices
• Comfortable in writing C++ code to help integrate with our autonomous vehicle platform.
• 5+ years of experience with deep learning approaches such as supervised/unsupervised learning, transfer learning, multi-task learning, and/or deep reinforcement learning.
• Extensive experience with learning-based planning approaches like imitation learning, reinforcement learning and state-of-the-art techniques for sequential modeling like Transformer architectures.
• 5+ years of experience covering machine learning workflows, data sampling and curation, pre-processing, model training, ablation studies, evaluation, deployment, and inference optimization.
• Passionate about self-driving car technology and its potential for humanity.
• Strong communication skills with the ability to communicate concepts clearly and precisely.

NICE TO HAVES

• Published research at top-tier conferences (NeurIPs, RSS, IROS, ICRA, and similar).
• Proven track record of deploying ML models at scale in self-driving or related fields.
• Familiarity with production-level coding in time-limited task schedules.
• Experience with robot motion planning (e.g., trajectory optimization, sampling-based planning, model predictive control) 
• Experience with temporal data and/or sequential modeling.
• Experience in self-driving challenges (Perception, Prediction, Planning, Simulation).