Manager, Behavior Foundation Model

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8 days old

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The Prediction & Behavior ML team is responsible for developing machine learning (ML) algorithms that learn and predict behaviors from data, applying them both on-vehicle to influence driving behavior and off-vehicle to provide ML capabilities to simulation and validation. Given the tight integration of behavior forecasting and motion planning, our team collaborates closely with the Planner team to advance overall vehicle behavior. We also work closely with our Perception, Simulation, and Systems Engineering teams  to accelerate our ability to validate our driving performance.

As an Engineering Manager for the Behavior Foundation Model team, you will lead the team responsible for advancing and scaling foundation models that understand and generate driving behaviors. This team collaborates  across Perception, Planning, SImulation, Data Science, Systems Engineering, Validation, QA, and ML Infra, to leverage the power of generative AI for applications, including: scene encoding for learned driving trajectories, automated driving quality assessment, estimating scenario similarity, synthetic scenario creation, and simulated agent behavior. There are also emergent applications building on these technologies that will expand over time.

In this role, you will:

  • Team Leadership: Manage, mentor, and grow a team of managers and technical leads, fostering a culture of innovation and continuous improvement.
  • Strategy Development: Develop and organize our overall strategy for Foundation Models as they relate to driving behavior and scenario understanding. You will interface with multiple partner teams to identify opportunities for Foundation Model adoption within their problem area. You’ll be setting the short and long term technical direction for the team and collaborate on the broader company-wide directions.
  • Technical Oversight: Provide technical guidance and leadership in the design and development of training large, multi-modal foundation models and work with partner teams on ensuring their efficient inference.
  • Performance Monitoring: Establish and monitor key performance indicators (KPIs) to measure the effectiveness of optimization strategies and drive continuous improvement.
  • Resource Management: Manage the allocation of resources within the team, ensuring that projects are staffed appropriately and that team members have the necessary tools and support to succeed.

    • Qualifications:

  • Fluency in  Python
  • Extensive experience with programming and algorithm design, strong mathematics skills
  • BS, MS, or PhD degree in computer science or related field
  • 5+ years of experience with production Machine Learning pipelines, with at least 2 years in a leadership or management role.
  • Expertise with some, or all, of Large Language Models, Diffusion, Reinforcement Learning, and ML for Planning

    • Bonus Qualifications

  • Conference or Journal publications in Machine Learning or Robotics related venues
  • Prior experience working with autonomous vehicles or robotics
    • Compensation and Benefits
    There are three major components to compensation for this position: salary, Amazon Restricted Stock Units (RSUs), and Zoox Stock Appreciation Rights. The salary range for this position is $230,000 to $332,000. A sign-on bonus may be offered as part of the compensation package. Compensation will vary based on geographic location and level. Leveling, as well as positioning within a level, is determined by a range of factors, including, but not limited to, a candidate's relevant years of experience, domain knowledge, and interview performance. The salary range listed in this posting is representative of the range of levels Zoox is considering for this position. 

    Zoox also offers a comprehensive package of benefits including paid time off (e.g. sick leave, vacation, bereavement), unpaid time off, Zoox Stock Appreciation Rights, Amazon RSUs, health insurance, long-term care insurance, long-term and short-term disability insurance, and life insurance.


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