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.
- You will write algorithms to process raw sensor data, track dynamic agents, and predict the future state for agents
- You will apply distributed compute algorithms to efficiently analyze petabytes of urban driving data
- You will develop metrics and tools for analyzing errors and understanding improvements in our systems
- You will engineer software that runs on-vehicle to efficiently execute our algorithms in real time
- You will engineer software that is fault-tolerant and conforms to automotive safety standards
- You will collaborate with engineers on the other parts of CAS Perception, CAS Verification & Validation, CAS Planner, and the Main AI teams to solve the overall Autonomous Driving problem in complex urban environments
- BS, MS, or PhD degree in computer science or related field
- Fluency in C++
- Extensive experience with programming and algorithm design
- 8+ years of experience in a related field
- Experience with production Machine Learning pipelines: dataset creation, training frameworks, metrics pipelines
- Experience with latency of analysis and optimization of safety critical software systems
- Experience with petabyte-scale distributed computing (Spark, Databricks, generic MapReduce pipelines)
- CUDA programming experience
- 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 $210,000 - $300,000. 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.Vaccine Mandate
Employees working in this position will be required to have received a single dose of the J&J/Janssen COVID-19 vaccine OR
have completed the two-dose Pfizer or Moderna vaccine series. In addition, employees will be required to receive a COVID-19 booster vaccine within two months of becoming eligible for the booster vaccine.
Employees will be required to show proof of vaccination status upon receipt of a conditional offer of employment. That offer of employment will be conditioned upon, among other things, an Applicant’s ability to show proof of vaccination status. Please note the Company provides reasonable accommodations in accordance with applicable state, federal, and local laws.About Zoox
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.Follow us on LinkedInA 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.