Senior Data Operations Manager - Data Operations Lead

United States·Boston,Foster CityFull-timelead

OperationsOtherTechnical Program ManagerOperations LeadData Operations Manager

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pandaspythonsqlmachine-learningproject-management

We are seeking an experienced and highly skilled operations leader to join the Perception Data and Labeling team. The team is responsible for training and evaluation data powering the perception (vision, lidar, and other modalities) ML models at Zoox. The candidate will work alongside ML engineers, product owners, data engineers, and external partners to scope and deliver high-quality training and evaluation data to help the Zoox Perception AI team meet critical deadlines.

Translate and coalesce company-wide feature requirements into concrete and comprehensive data deliverables

Work collaboratively with AI teams, project management, and data annotation teams to manage the collection and labeling of training and evaluation data powering Zoox’s AI perception stack.

Manage vendor allocation and budgeting in conjunction with the milestone and release timelines at Zoox.

Define and maintain clear tracking of outcomes, risk, and data quality to ensure transparency and accountability.

Experience in Technical Program Management or Operations Strategy: 5+ years of experience managing complex, cross-functional programs within the technology, autonomous driving, or AI/ML sectors.

Perception & Sensor Domain Knowledge: Strong understanding of the machine learning development lifecycle (MLDL) and familiarity with autonomous vehicle sensor modalities (LiDAR, Radar, Camera, Thermal) and their respective data annotation requirements.

Strategic Capacity Planning: Demonstrated ability to translate high-level product roadmaps and engineering requirements into granular operational execution plans. Experience managing resource allocation and throughput for large-scale workflows.

Vendor Ecosystem Understanding: Experience overseeing large-scale vendor operations or managed service providers, specifically regarding quality, latency, and volume targets.

Data Literacy: Proficiency with SQL or Python/Pandas to query databases, analyze throughput metrics, and generate reports without needing engineering support.