Senior Data Scientist - Verification & Validation

Zoox has embarked on a highly ambitious journey to develop a full-stack autonomous mobility solution for our cities. As a technical program manager, you will work cross-functionally with engineering leaders across software, hardware, vehicle engineering, and product to drive our corporate strategy into tactical and detailed road maps that facilitate effective execution at each stage of our growth curve. You will work with each engineering team to develop project schedules, identify milestones, flag risks, estimate budgets, and clearly communicate ongoing progress. In this role, you will: Partner with Autonomy V&V engineering managers to translate the top-down corporate strategy and milestones into detailed product roadmaps, timelines, and deliverables You'll drive and support teams of software engineers and data engineers/scientists to stand up cutting-edge evaluation pipelines leveraging statistics, simulation, and other methods You'll play a defining role in building scalable systems that improve how we evaluate autonomy behavior at Zoox You'll work with cross-functional stakeholders to proactively identify gaps, escalate risks, drive bug closure, and contribute to test coverage tracking You'll be a trusted partner to engineering leadership and the go-to person for unblocking teams and driving solutions Qualifications BS/MS degree in computer science, engineering or equivalent job experience At least 6 years of experience in engineering program management Strong track record of managing complex cross-functional projects and problem-solving An ability to keep the big picture in focus and to provide clear, well-structured, and concise communications tailored to each appropriate audience Deep familiarity with software development processes & proficiency in tools or processes required to manage complex projects (i.e. Gantt

Perception data is core to how Zoox’s robotaxis understand the world, and as Senior Manager of Perception Data, you will own the flywheel that turns that data into safer, smarter driving. You will lead our perception data organization, spanning data science, data engineering, and data labeling, and own how we mine logs, automate annotation, feed high value data into our models, and close the loop through analysis and measurement. The most valuable examples in our corpus are often the hardest to find: rare behaviors, unusual interactions, safety critical events, and the long tail of real world urban driving. Your role is not only to build the systems that process this data, but to decide what data matters and why, and to build the learning loop that lets Zoox improve model performance faster. This is an opportunity for a leader who blends strategic thinking with strong execution, has done it before at scale, and knows how to partner with ML leaders, metrics pipelines, and infrastructure teams. In this role, you will... Own the perception data flywheel. Run the learning loop from real world fleet signals and model behavior through data discovery, curation, and enrichment into training, evaluation, and measurement. Lead multidisciplinary teams. Manage and develop a 10+ person team of data science, data engineering and data labeling, setting priorities and raising the bar on execution. Automate annotation at scale. Drive auto annotation and auto labeling pipelines, reducing manual cost while improving label quality and throughput. Build advanced data miners. Develop intelligent approaches to surfacing rare, surprising, and safety critical scenarios in very large datasets, using techniques such as embeddings, semantic search, learned representations, and model driven data selection. Own log selection and storage. Define how we select, store, and retrieve fleet logs so the right data reaches our models efficiently and economicall

The Program Management Office (PMO) at Zoox is responsible for driving cross-functional program planning and execution at the highest level. We partner with leaders from across the company in vehicle development, system design, software engineering, manufacturing, fleet operations, and business functions to develop and deliver major corporate milestones on the path to launch, and beyond. Our program managers contribute to the end to end success of technical, integrated product milestones involving both of our vehicle platforms - the Toyota Highlander test fleet and Zoox’s purpose-built robotaxi. In this role, you will: Own the fleet validation operational strategy: Lead the end-to-end strategy and execution of mileage accumulation for both the physical test fleet and simulation assets, to enable Zoox’s geofence expansion across all cities. Partner closely with upstream teams (e.g. Autonomy, Systems Design & Mission Assurance, Places & Build) and downstream teams (e.g. Data Science, Fleet Operations) to ensure critical inputs are available, and results are delivered; you will ultimately "own the outcome" of test fleet data collection. This is a high leverage, high impact role. Usher in a simulation-first methodology : Act as the cross-functional catalyst for scaling simulated mileage accumulation. Drive alignment between Autonomy, System Design & Mission Assurance, and Simulation teams to ensure clear requirements are set, and simulation platforms are resourced to meet exponentially growing data needs. Identify and resolve critical bottlenecks : Develop rigorous tracking mechanisms that model the impact of upstream dependencies (e.g., map content deliverables and safety requirements). You’ll think critically and work cross-functionally to squash inefficiencies in upstream and downstream pipelines and systems. Partner collaboratively wi

The Perception team at Zoox is responsible for the robot’s understanding of the world, fusing data from Lidar, Radar, and Cameras to create a unified representation of the environment. In this role, you will contribute to the development of our next-generation 3D occupancy and segmentation networks. You will architect and optimize high-performance deep learning models that generate dense, temporally consistent voxel representations of the driving environment. This work is critical for enabling our vehicle to navigate complex urban scenarios, handle rare obstacles, and drive safely in tight spaces by providing precise geometry and motion estimates to downstream planners. In this role, you will... Design and implement state-of-the-art multi-modal sensor fusion architectures (Lidar, Camera, Radar) to predict 3D occupancy, semantic segmentation, and flow . Develop "vision-first" fusion strategies to enhance geometric understanding and reduce dependency on sparse sensor modalities . Engineer temporal processing modules to improve the stability and consistency of predictions over time. Optimize model architectures for real-time on-vehicle inference, balancing high-fidelity range extension with strict latency constraints . Collaborate with downstream consumers (Tracking, Prediction, Planner) to refine geometric outputs, such as contours and free-space estimations, for complex maneuvering. Qualifications MS or PhD in Computer Science, Robotics, Machine Learning, or related field with 6+ years of industry experience. Deep expertise in 3D Computer Vision and Deep Learning, specifically with voxel-based or BEV (Bird's Eye View) architectures. Strong proficiency in Python and deep learning frameworks (PyTorch) for model training and design as well as some experience in C++ for model integration. Experienc

The Prediction & Behavior ML team is responsible for developing machine learning (ML) algorithms that learn and predict behaviors from data, applying them both on-vehicle to influence driving behavior and off-vehicle to provide ML capabilities to simulation and validation. Given the tight integration of behavior forecasting and motion planning, our team collaborates closely with the Planner team to advance overall vehicle behavior. We also work closely with our Perception, Simulation, and Systems Engineering teams to accelerate our ability to validate our driving performance. As a Learned Trajectory Machine Learning Engineer you will be responsible for developing deep learned models that produce trajectories for our vehicles to drive. Given the tight integration of behavior prediction and motion planning, you will closely collaborate with the Planner and Perception teams in the advancement of our overall vehicle behavior. In this role, you will: You will develop new deep learning models that use imitation learning and reinforcement learning to generate driving plans for our autonomous vehicle. You will also work on techniques to estimate the quality of those driving plans along the dimensions of safety, progress, comfort etc. You will leverage our large-scale machine learning infrastructure to discover new solutions and push the boundaries of the field You will develop metrics and tools to analyze errors and understand improvements of our systems You will collaborate with engineers on Perception, Planning, and Simulation to solve the overall Autonomous Driving problem in complex urban environments Qualifications BS, MS, or PhD degree in computer science or related field Experience with training and deploying transformer-based model architectures and reinforcement learning Experience with production Machine Learning pipelines: dataset creation, training frameworks, metrics pipelines Fluency in Pyt

The Zoox 3D Sensor Simulation team’s work is at the core of creating in-the-loop simulation and high fidelity synthetic data for training and testing autonomous vehicle AI. We are looking for a machine learning professional with experience applying ML to sensor data, such as LiDAR, radar, and cameras. This role lies at the intersection of machine learning and 3D simulation at Zoox, ranging from learned sensor models to neural 3D reconstruction. By improving the realism of simulated sensors (lidar, radar, and cameras), you’ll enable the Zoox robotics autonomy stack to learn, improve, and enhance the mobility of humans. In this role, you will: Design, train, and validate ML models that improve the realism of simulated lidar, radar, and camera data in autonomous vehicle (AV) simulation pipelines. Collaborate with Synthetic Data and HIL Sim teams to integrate 3DGS and NeRF-based 3D reconstruction with simulation of all sensor modalities. Build and curate training datasets from real and simulated sensor data, including GenAI-based data augmentation. Partner with Sim V&V and Perception engineers to define sensor realism metrics and close the sim-to-real gaps with the greatest impact on autonomy. Mentor engineers and interns, and establish best practices for training and deploying ML on Zoox sensor data. Qualifications: 2+ years of prior experience as a Technical Lead 5+ years of experience developing ML models in Python with PyTorch or TensorFlow <