Jobs at Zoox

The Operations Lead will manage the Perception Data team, overseeing data collection and labeling for AI models, ensuring high quality and timely delivery while working with ML engineers and external partners.

Design and implement quantitative behavior metrics for autonomous vehicles, build and maintain data pipelines and dashboards, analyze large-scale vehicle logs and simulation data to identify regressions, set metric thresholds to support geofence expansion, and communicate findings to technical and non-technical stakeholders.

As a Senior/Staff Software Engineer, you will improve robotic driving behaviors through algorithm development, testing, and performance reviews while ensuring safety and innovation.

Lead the development of machine learning algorithms focusing on perception for autonomous driving, collaborating across teams and mentoring ML developers.

The Software Engineer will develop algorithms and code related to AI, robotics, and sensing technologies, impacting key systems at Zoox.

Develop advanced Vision-Language-Action models for robotaxis, leading data strategies and improving driving behaviors using machine learning infrastructure.

Develop and integrate detection, tracking, classification, and scene-understanding ML models for on-vehicle perception. Define and implement on-vehicle tracking architecture, collaborate with model and data teams, optimize models for high-performance vehicle deployment, and work with perception input/output data.

Design and develop auto-labeling algorithms for autonomous driving, collaborating with ML engineers to enhance data quality and efficiency in model training.

Lead strategic sourcing and supplier partnerships for vehicle direct materials and operations infrastructure. Drive RFQs, negotiations, contract management, supplier performance, cost reduction initiatives, total cost of ownership models, and cross-functional stakeholder alignment to support vehicle development and autonomous ride-hailing operations.

As a Senior Software Engineer - C++ GPU Performance, you will optimize GPU algorithms, monitor performance metrics, and influence design decisions for self-driving technology.

Lead data-quality and labeling efforts for perception ML: implement scalable quality measures, drive data-centric model improvements, maintain ontology/class structure, evaluate human vs auto-labeling trade-offs, and build metrics for labeling throughput and annotator/vendor quality.

The role involves optimizing GPU-based algorithms, developing benchmarking frameworks, analyzing performance metrics, and facilitating efficient code development for autonomous vehicle systems.

Design and optimize on-vehicle perception inference: allocate CPU/GPU resources, compress and quantize large multimodal models, build TensorRT model conversion pipelines, and deliver production-quality low-latency C++/CUDA inference for power- and thermal-constrained vehicle SoCs.