Hybrid opportunity at
ZooxSenior/Staff Software Engineer - Behavior Capabilities
Zoox is currently seeking a Senior or Staff Software Engineer to join the Behavior Capabilities function inside the Fail Operational Planning division. The organization is building…
Career Tools
About This Role
Zoox is currently seeking a Senior or Staff Software Engineer to join the Behavior Capabilities function inside the Fail Operational Planning division. The organization is building a purpose-built, fully autonomous vehicle fleet along with the infrastructure needed to deploy this mobility-as-a-service technology into urban environments. This position focuses on ensuring that the autonomous vehicle functions effectively even when minor, compartmentalized failures or reduced capabilities occur. Professionals on this team build…
Job Description
Zoox is currently seeking a Senior or Staff Software Engineer to join the Behavior Capabilities function inside the Fail Operational Planning division. The organization is building a purpose-built, fully autonomous vehicle fleet along with the infrastructure needed to deploy this mobility-as-a-service technology into urban environments. This position focuses on ensuring that the autonomous vehicle functions effectively even when minor, compartmentalized failures or reduced capabilities occur. Professionals on this team build motion planning and behavioral algorithms designed to elevate vehicle uptime, improve trip progress, and enhance the overall rider experience.
This role is well-suited for engineers who want to solve complex technical challenges by understanding the interdependencies across a complete driving stack. Individuals in this position will take ownership of their assignments and maintain a broad, product-oriented development mindset. Team members work alongside diverse specialists spanning Perception, Prediction, Hardware, and Planning disciplines. Candidates will help shape next-generation algorithmic progress, allowing autonomous vehicles to navigate highly intricate driving environments safely and reliably.
Responsibilities
- Develop principled algorithmic enhancements for targeted driving behaviors and integrate these updates into the codebase
- Work collaboratively across teams to build strategies and smart behaviors that lessen performance drops during various system failure modes
- Design and build scalable software solutions that integrate smoothly with the remainder of the autonomous driving stack
- Work alongside validation groups to plan and carry out testing for newly created algorithms
Requirements
- Hold a Master's degree in Computer Science or a related technical field
- Possess nine or more years of professional experience
- Demonstrate fluency in the C++ programming language
- Bring extensive background in algorithm design and programming
- Possess an understanding of vehicle kinematics
Qualifications
- Hold a PhD in Electrical Engineering, Computer Science, Mechanical Engineering, or a related discipline
- Bring past experience launching products into commercial markets, such as consumer electronics, drones, or commercial robotics
- Show a proven capability to develop real-time motion planning algorithms within a cross-functional team environment
Core Skills
Frequently Asked Questions
What team does this position belong to?
This role is part of the Fail Operational Planning team under the Behavior Capabilities group at Zoox.
What are the core educational and experience requirements?
Candidates must have a Master's degree in Computer Science or a related field, alongside nine or more years of experience, fluency in C++, and knowledge of vehicle kinematics.
What is the salary for this position?
The provided job posting does not specify salary information.
Where is this job located and is it remote?
The specific job location is not stated in the source posting, but the remote status is listed as hybrid.
What is the employment type?
The employment type is full-time.
Sample Interview Questions
AI-generated questions tailored to this specific role — a preview of the full practice set.