Zoox
From Zoox's careers page
Status: listed on the employer's own careers page when we last checked (daily). Confirm on their site before applying.
In this role, you will: Apply distributed computing algorithms to analyze petabytes of urban driving data.
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 Artificial Intelligence (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 multidisciplinary 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.
Apply distributed computing algorithms to analyze petabytes of urban driving data.
Develop metrics and tools to analyze errors and system improvements.
Work closely with CAS engineers to evaluate system performance.
Collaborate with Perception engineers to define metrics for autonomous driving.
Fluency in C++ and/or Python
Experience with petabyte-scale distributed computing (Spark, Databricks, generic MapReduce pipelines)
Background in Bayesian statistics
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