Staff Machine Learning Engineer, Behavior Planning & Prediction
- 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.
- 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.
- 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).
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