The Scene Understanding Semantic Reasoning team at Zoox builds the high-performance reasoning engines that allow our autonomous vehicles to navigate complex driving environments and high-speed roads. We translate sensor data and detected objects into deep semantic understanding, ensuring our robots make human-level decisions in real-time.
We are seeking experienced engineers passionate about the intersection of robotics and cutting-edge AI. In this role, you will focus on critical initiatives alongside partner Perception and motion planning teams to develop production-grade multi-task transformers, and integrate cutting-edge Vision Language Action (VLA) model outputs to build comprehensive spatial representations for our fleet. You will tackle the inherent unpredictability of urban driving on highways & freeways to improve range and accuracy, ensuring our vehicles remain safe and resilient at all times.
In this role, you will...
Model Training & Deployment: Design, train, and deploy deep learning models for semantic reasoning, specifically tailored to achieve the extended spatial range and high fidelity required for high-speed highway environments.
Cross-Functional Collaboration: Collaborate with the Scene Intelligence, Semantic Grounding, and PCP Mapping teams to adapt and elevate the unified machine learning stack for highway scenarios.
Requirements & Validation: Partner with downstream motion planning teams to define semantic representation requirements, establish robust validation workflows, and ensure model outputs meet strict safety and clearance metrics.
Optimization: Optimize deep learning models for real-time inference efficiency, ensuring low-latency execution within the rigorous compute constraints of the Zoox vehicle platform.
Edge Case Resolution: Investigate and resolve perception-related regressions and edge cases found in high-speed driving simulations and live fleet data.
Strategic Architecture: Contribute to the long-term "North Star" architecture for Perception Semantic Reasoning, paving the way for scalable fleet deployment across new vehicle platforms.
Qualifications
MS (3–5 years) or PhD (0–2 years) in Computer Science, Robotics, Electrical Engineering, or a related field, with professional software engineering experience — ideally in autonomous driving, robotics, or computer vision.
Deep understanding of 2D/3D computer vision, semantic segmentation, and deep learning architectures.
Exceptional programming skills in modern C++ and Python.
Hands-on experience with modern deep learning frameworks like JAX or PyTorch.
Proven track record of deploying real-time machine learning models on resource-constrained embedded systems or on-bot hardware.
Bonus Qualifications
Prior experience dealing with highway autonomous driving scenarios and their specific mapping/perception challenges.
Familiarity with state-of-the-art, BEV, Sparse Transformer architectures and Vision-Language Models (VLMs).
Strong publication record in top AI conferences or journals (e.g., CVPR, ICCV, ECCV, ICML, NeurIPS).
Skills Required
- MS in Computer Science, Robotics, Electrical Engineering, or a related field
- 3-5 years of professional software engineering experience, ideally in autonomous driving, robotics, or computer vision
- Deep understanding of 2D/3D computer vision, semantic segmentation, and deep learning architectures
- Exceptional programming skills in modern C++ and Python
- Hands-on experience with JAX or PyTorch
- Proven track record of deploying real-time machine learning models on embedded systems
- PhD in a related field with 0-2 years experience
- Prior experience in highway autonomous driving scenarios
- Familiarity with BEV, Sparse Transformer architectures and Vision-Language Models
- Strong publication record in top AI conferences or journals
Zoox Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Zoox and has not been reviewed or approved by Zoox.
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Healthcare Strength — Healthcare is extensive, with broad medical and vision options, company‑paid disability coverage, and multiple mental‑health resources. Feedback suggests coverage breadth and auxiliary programs support a wide range of needs.
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Parental & Family Support — Family supports include paid parental leave, additional pregnancy disability time, fertility coverage, and adoption/surrogacy assistance. Backup care and family‑oriented programs further reinforce support across life stages.
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Wellbeing & Lifestyle Benefits — Day‑to‑day perks are robust, including free daily meals, fitness subsidies, commuter support, and on‑site amenities. Feedback suggests these lifestyle benefits enhance convenience and workplace experience, especially for office‑based roles.
Zoox Insights
What We Do
Zoox is an autonomous mobility company that was founded to provide a safer, cleaner, and more enjoyable future on the road. To achieve that goal, the company has spent the past 10 years creating a purpose-built robotaxi that gives the world a better way to ride.
Why Work With Us
At Zoox, we are working to solve one of the greatest technological challenges of our generation. From the beginning, we have been focused on our goal of reimagining transportation from the ground up. We are a mission-driven community of innovators working together to create a safer, cleaner, and more enjoyable future on the road.
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