Salary
$324k – $389k per year
Location
In office (Foster City)
Seniority
Staff
Employment
Full-Time
Overview
Company
Impact
Profile match
Zoox is an American technology company headquartered in Foster City, California, that was founded in 2014. The company develops a purpose-built, fully autonomous electric vehicle designed specifically for ride-hailing services rather than individual ownership. Operating as an independent subsidiary of Amazon, the firm is currently testing its robotaxi fleet in several major United States cities including San Francisco and Las Vegas.
At Zoox, you will collaborate with a team of world-class engineers with diverse backgrounds in areas such as AI, robotics, mechatronics, planning, control, localization, computer vision, rendering, simulation, distributed computing, design, and automated testing. You’ll master new technologies while working on code, algorithms, and research to impact key systems to move Zoox forward.
Responsibilities
- Lead the Sensor Change Playbook workflow, defining the validation process for our next-generation, low-cost vehicle platforms.
- Partner with PCP V&V to define the Autonomy Technical Specification (ATS) by identifying "bounding" (worst-case) scenarios, particularly those related to winter driving (e.g., heavy snow, ice, sensor occlusion).
- Work with PCP model owners to architect low-cost stacks that reduce reliance on expensive sensors and accommodate reduced compute (e.g., migrating from 8 GPUs to 1 Thor).
- Drive the Clearance MoC (Method of Compliance) process for hardware changes, balancing cost, compute constraints, performance and safety.
Qualifications
- Deep expertise in the PCP Stack, multi-modality fusion, and optimizing architectures for severely constrained compute budgets.
- Experience in V&V (Validation & Verification) for safety-critical systems, specifically expanding into complex Operational Design Domains (ODDs) like winter weather.
- Proven ability to influence cross-functional stakeholders (SDMA, AHE, PCP) to align on cost vs. performance trade-offs.
- The ability or experience of managing or curating datasets for sensor validation or model training
Bonus Qualifications
- Experience with Autonomy Technical Specifications (ATS) and defining winter/adverse weather bounding scenarios.
- Experience working with VLM’s.
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