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Zoox is seeking a Senior Manager of Perception Data to lead the organization responsible for turning raw fleet data into safer, smarter autonomous driving. You will own the complete perception data flywheel—from mining logs and automating annotation to feeding high-value data into models and closing the loop through rigorous analysis and measurement.
Perception data is foundational to how Zoox's robotaxis understand the world. The most valuable examples in the 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 combines strategic thinking with hands-on execution: you will decide what data matters and why, then build the learning loop that accelerates model performance improvement.
You will lead a multidisciplinary team of 10+ people spanning data science, data engineering, and data labeling. Key responsibilities include:
• Own the perception data flywheel, running the complete learning loop from fleet signals and model behavior through data discovery, curation, and enrichment into training, evaluation, and measurement.
• Lead and develop high-performing technical teams, setting priorities and raising execution standards.
• Drive automation of annotation at scale, reducing manual cost while improving label quality and throughput.
• Build advanced data mining approaches to surface rare, surprising, and safety-critical scenarios in massive datasets using embeddings, semantic search, learned representations, and model-driven data selection.
• Define how fleet logs are selected, stored, and retrieved to ensure the right data reaches models efficiently and economically.
• Establish rigorous measurement of data value and make informed trade-offs across quality, accuracy, speed, cost, and scale.
• Feed curated data into model training and evaluation, then analyze outcomes to continuously refine collection and labeling strategies.
• Partner closely with ML, metrics, evaluation, and infrastructure teams to maintain reliable, scalable operations.
This role requires a leader who has done this before at scale and knows how to partner effectively with ML leaders, metrics pipelines, and infrastructure teams.
QUALIFICATIONS:
• Track record of building and leading high-performing technical teams (data science, data engineering, ML, or labeling), including managing managers or senior individual contributors.
• Deep technical expertise in computer vision, video, multimodal AI, or related perception problems.
• Experience leading large-scale data capabilities that directly influence model training, evaluation, and performance.
• Strong intuition for what makes data valuable, with hands-on experience in data discovery, selection, curation, and enrichment at scale.
• Proven execution at scale with strong technical and commercial judgment across quality, speed, cost, and build-versus-buy trade-offs.
• Ability to move fluidly between strategy and technical detail, set direction in ambiguity, and influence senior technical and business stakeholders.
BONUS QUALIFICATIONS:
• Background in autonomous driving, robotics, or embodied AI.
• Experience with large-scale video, multimodal, or foundation model training.
• Expertise in semantic search, embeddings, active learning, auto-labeling, or intelligent data selection and enrichment.
• Experience acquiring large-scale real-world data across fleets, partners, or multiple geographies.
