Hybrid opportunity at
ZooxSoftware Engineer - Collision Avoidance System Metrics
Zoox is building a ground-up, fully autonomous vehicle fleet along with the ecosystem needed to launch this technology into the market, combining robotics, machine learning, and…
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About This Role
Zoox is building a ground-up, fully autonomous vehicle fleet along with the ecosystem needed to launch this technology into the market, combining robotics, machine learning, and design to deliver next-generation urban mobility-as-a-service. The Collision Avoidance System (CAS) operates in parallel to the primary AI autonomy stack, utilizing a blend of deep learning and geometric algorithms to detect impending obstacles within dense city settings while respecting strict computing limits. Within this…
Job Description
Zoox is building a ground-up, fully autonomous vehicle fleet along with the ecosystem needed to launch this technology into the market, combining robotics, machine learning, and design to deliver next-generation urban mobility-as-a-service. The Collision Avoidance System (CAS) operates in parallel to the primary AI autonomy stack, utilizing a blend of deep learning and geometric algorithms to detect impending obstacles within dense city settings while respecting strict computing limits. Within this division, the CAS Verification and Validation group consists of systems, software, and data engineers who formulate performance metrics and collaborate alongside quality assurance and design teams to construct validation strategies.
This position centers on measuring and evaluating the effectiveness of the Collision Avoidance System using large-scale data analysis. Professionals in this role will process massive urban driving datasets, build diagnostic metrics, and coordinate closely with perception and planning engineering units. The ideal candidate brings strong programming capabilities and a solid foundation in computer science.
Zoox seeks individuals who want to contribute to a fast-moving, execution-focused environment and welcomes applicants even if they do not meet every single listed expectation.
Responsibilities
- Analyze petabytes of driving data from urban environments utilizing distributed computing algorithms
- Design and build tools and metrics to assess errors and track system enhancements
- Partner with CAS engineers to assess overall system performance
- Coordinate with perception engineers to formulate autonomous driving metrics
- Work alongside planning engineers to evaluate performance in complicated city settings
Requirements
- Fluency in Python, C++, or both languages
- Extensive background in algorithm design and programming
Qualifications
- BS, MS, or PhD in computer science or a related discipline
- Familiarity with safety-critical software system latency analysis
- Experience handling petabyte-scale distributed computing systems such as Spark, Databricks, or general MapReduce pipelines
- Knowledge of Bayesian statistics
Core Skills
Frequently Asked Questions
What is the remote work policy for this position?
The posting indicates that the position is hybrid.
What are the core educational requirements?
Applicants should hold a BS, MS, or PhD degree in computer science or a closely related field.
What technical programming skills are required?
Candidates must have extensive experience with programming and algorithm design, including fluency in C++ and/or Python.
What is the salary range for this role?
The job posting does not specify the salary for this position.
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