The Collision Avoidance System (CAS) is responsible for detecting and reacting to imminent collision situations in support of our vehicle's overall safety goals. CAS Perception is responsible for processing raw sensor data from our vehicle's world-class sensor suite using a combination of geometric, interpretable algorithms and deep learning to detect near-collisions with obstacles along our intended driving path, in the most challenging dense urban environments and under tight compute resource constraints. Overall CAS is parallel and complementary to our Main AI autonomy stack and has a close relationship with our vehicle hardware and safety teams to architect redundancy into our overall driving system.As the Manager, Data Science for CAS (CAS Verification and Validation) at Zoox, you will spearhead a multifaceted team comprising engineers, data scientists, and statisticians, focusing on the critical task of assessing the Collision Avoidance System (CAS). This system is essential for detecting and mitigating imminent collisions, through partnering with Zoox's autonomy software teams. Your role involves defining and building metrics to gauge CAS performance, emphasizing its operation in dense urban settings. You will collaborate extensively with System Engineers and QA teams to formulate comprehensive validation plans, ensuring CAS's efficacy and integration within Zoox's broader safety objectives.ResponsibilitiesYou will set the short and long-term technical direction for the team and collaborate on the broader company-wide directions You will coordinate cross-functional initiatives with other teams across CAS Perception Algorithms, Systems Engineering, QA, and moreYou will grow the team through hiring and guide the continued professional development of team membersYou will collaborate with engineers on the other parts of CAS Perception, CAS Planner, and the Main AI teams to solve the overall Autonomous Driving problem in complex urban environmentsQualificationsB.S. or higher degree in an Engineering or Science discipline with a strong focus on Mathematics, Statistics, Probability Theory, or Data Science8+ years of relevant professional work experience and at least 2 years of leading teams of 5+ engineersFluency in PythonProficiency in quantitative analysis/modeling toolsSound statistical inference skills, with the ability to communicate uncertainty appropriately to engineering and business stakeholdersBonus QualificationsAdvanced Degree in Computer ScienceExperience with production metrics pipelinesExperience with manual or automatic labeling pipelinesExperience with analysis of latency for safety-critical software systemsExperience with petabyte-scale distributed computing (Spark, Databricks, generic MapReduce pipelines)Background in Bayesian statisticsProficient with Scala / R / SQLPrior experience with autonomous vehicles in generalStrong mathematics skillsCompensationThere are three major components to compensation for this position: salary, Amazon Restricted Stock Units (RSUs), and Zoox Stock Appreciation Rights. The salary will range from $203,000 to $319,000. A sign-on bonus may be part of a compensation package. Compensation will vary based on geographic location, job-related knowledge, skills, and experience. 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.About ZooxZoox is developing the first ground-up, fully autonomous vehicle fleet and the supporting ecosystem required to bring this technology to market. Sitting at the intersection of robotics, machine learning, and design, Zoox aims to provide the next generation of mobility-as-a-service in urban environments. We're looking for top talent that shares our passion and wants to be part of a fast-moving and highly execution-oriented team.Follow us on LinkedIn AccommodationsIf you need an accommodation to participate in the application or interview process please reach out to ****** or your assigned recruiter.A Final Note:You do not need to match every listed expectation to apply for this position. Here at Zoox, we know that diverse perspectives foster the innovation we need to be successful, and we are committed to building a team that encompasses a variety of backgrounds, experiences, and skills.
