Manager, Offline Driving ML
7 Months ago • 5 Years + • $230,000 PA - $317,000 PA
Research Development
Job Description
The Offline Driving Intelligence team develops machine learning algorithms for training driving models using large-scale data, focusing on predicting behaviors and planning. This role involves managing and mentoring a team, developing strategy for offline ML models, and providing technical leadership in designing and developing training models. Responsibilities include fostering innovation, setting technical direction, collaborating with partner teams, and monitoring key performance indicators. The ideal candidate will have expertise in Reinforcement Learning, ML for Planning, strong programming and mathematics skills, and experience with production ML pipelines, including leadership experience.
Good To Have:
- Conference or Journal publications in ML or Robotics
- Experience with autonomous vehicles or robotics
- Experience with diffusion models
- Experience with large scale training
Must Have:
- Expertise with Reinforcement Learning and ML for Planning
- Extensive experience with programming and algorithm design
- Strong mathematics skills
- 5+ years of experience with production ML pipelines
- At least 2 years in a leadership or management role
Perks:
- Paid time off
- Unpaid time off
- Zoox Stock Appreciation Rights
- Amazon Restricted Stock Units
- Health insurance
- Long-term care insurance
- Long-term and short-term disability insurance
- Life insurance
The Offline Driving Intelligence team is responsible for developing machine learning algorithms that leverage data at large scale to train driving models. On the behaviors and planning team we learn and predict behaviors from large scale expert data and large scale reinforcement learning. This Offline Driving Intelligence team can leverage provided setups such as extended memory, flexible time and access to privileged information. The solutions developed are used in offline applications and to influence onboard decisions. This team is also building intelligent driving agents and dense driving metrics. In this role, you will collaborate closely with the Onboard Planning, Simulation, Perception, Validation, Data Science, Systems Engineering, QA, and ML Infra teams.
- Team Leadership: Manage, mentor, and grow a team of individual contributors, fostering a culture of innovation and continuous improvement.
- Strategy Development: Develop and organize our overall strategy for Offline ML Models for planning, behaviors and agents. You will interface with multiple partner teams to identify opportunities for 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 models at large scale 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.
- Expertise with Reinforcement Learning and ML for Planning.
- 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.
- Conference or Journal publications in Machine Learning or Robotics related venues.
- Prior experience working with autonomous vehicles or robotics, diffusion models, large scale training.
$230,000 - $317,000 a year
Base Salary Range
There are three major components to compensation for this position: salary, Amazon Restricted Stock Units (RSUs), and Zoox Stock Appreciation Rights. A sign-on bonus may be offered as part of the compensation package. The listed range applies only to the base salary. 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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