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 in order to architect redundancy into our overall driving system.
The CAS Verification & Validation (CAS V&V) is a multi-disciplinary team data, software and systems engineers defining and building metrics to measure the Collision Avoidance System performance and work with the Systems Design and Mission Assurance (SDMA) and QA teams to develop validation plans for the features.
- You will apply distributed compute algorithms to efficiently analyze petabytes of urban driving data
- You will work closely with other CAS engineers to develop metrics and tools for analyzing errors and understanding improvements in our systems
- You will collaborate with engineers on Perception and Planning to define metrics for the overall Autonomous Driving problem in complex urban environments
- BS, MS, or PhD degree in computer science or related field
- Fluency in C++ and/or Python
- Extensive experience with programming and algorithm design
- Experience with production metrics pipelines
- Experience with manual or automatic labeling pipelines
- Experience with analysis of latency for safety critical software systems
- Experience with petabyte-scale distributed computing (Spark, Databricks, generic MapReduce pipelines)
- Background in Bayesian statistics
- Proficient with Scala / R / SQL
- Prior experience with Prediction and/or autonomous vehicles in general
- Strong mathematics skills
There 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 $180,000 to $256,000. 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.
Zoox 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.
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.