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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # SVP of Data Operations - **Company:** CNTXT CREATIVE INC - **Location:** Milpitas, CA, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Training Data, 3D Scanning, Artificial Intelligence, Motion Capture, DataOps, Data Streaming, Management of Software Versions, Embodied AI, Information Technology, Machine Learning Operations, Lidar - **Published:** November 7, 2026 - **Apply:** https://www.juju.com/job/28_25196_c9a9b28fa8490a826ab63634f318ee82 ## About the Role * 9+ years in operations leadership, including 7+ years running data annotation, data collection, or AI training data operations. * 5+ years at VP level or above, owning budgets of $50M+ and organizations of 200+ including vendor workforces. * Proven scaling of annotation or data collection programs to millions of labels or thousands of hours per month. * Direct experience with robotics data collection, teleoperation, or egocentric/wearable data capture. * Strong command of quality systems, workforce management, and vendor management at scale. * Working knowledge of ML data needs (dataset design, coverage, and how data quality affects model performance). * Experience with privacy, consent, and biometric data rules (CCPA/CPRA, GDPR, BIPA). * Bachelor's degree in Engineering, Computer Science, Operations, or a related field., * Experience at an autonomous vehicle, humanoid or industrial robotics, embodied AI, or foundation model company. * Background with leading annotation platforms or vendors (e.g., Scale AI, Labelbox, Encord, CVAT) or building in-house tooling. * Experience with VR teleoperation, motion capture, or haptic systems. * Experience running multi-site, multi-country collection operations, ideally spanning the US and the Middle East. * Experience with Arabic or multilingual data (speech, text, dialects) and sovereign or in-region data requirements. * Master's degree or MBA. ## Description The SVP of Data Operations owns the end-to-end engine that produces training data for CNTXT AI's AI and robotics models. This covers data annotation and labeling, real-world robotics data collection, egocentric (first-person video and sensor) capture, and teleoperation programs that generate demonstration data.You will scale these operations from pilot to industrial volume while raising quality and lowering cost per usable hour or label. You will lead in-house teams and vendor networks from our Milpitas headquarters and partner closely with research, robotics engineering, and ML infrastructure., Strategy and leadership * Define the multi-year data operations strategy, tied to model roadmaps and data needs from research. * Build and lead an organization spanning annotation, field collection, teleoperation, QA, and program management. * Decide build vs. buy for each data stream, and balance in-house teams with vendor capacity. * Build CNTXT AI's US data operations hub in Milpitas and run it as one operation with teams in the UAE and MENA, across time zones. Data annotation and labeling * Run large-scale annotation programs across image, video, 3D/point cloud, LiDAR, multimodal, and language data. * Own labeling guidelines, taxonomies, ontologies, and annotator training and calibration. * Manage annotation vendors and BPO partners on throughput, quality, cost, and security. * Bring in model-assisted and active-learning workflows to cut cost per label. Robotics data collection and teleoperation * Stand up and scale teleoperation programs that capture high-quality demonstration data for robot learning. * Manage teleoperator recruiting, training, scheduling, ergonomics, and performance, across shifts and sites. * Operate data collection labs and fleets, including robot uptime, hardware readiness, and task and scene design. * Work with robotics engineering on teleop rigs, VR/haptic interfaces, and collection tooling. Egocentric data capture * Run first-person data capture programs using head-mounted cameras, smart glasses, and wearable sensors. * Recruit and manage contributor networks for capture in homes, workplaces, and other real environments. * Ensure task, scene, and demographic diversity in line with research specifications. * Own informed consent, contributor agreements, and PII handling, including face and voice anonymization. Data quality, pipeline, and compliance * Set quality metrics (label accuracy, inter-annotator agreement, episode success rate, usable-hours yield) and hit them. * Partner with ML infrastructure on ingestion, metadata, curation, and dataset versioning. * Ensure compliance with CCPA/CPRA, GDPR, BIPA, UAE PDPL, data residency rules, and labor and contractor laws in every region where data is collected. Operational and financial excellence * Own the budget, unit economics (cost per labeled item, per teleop hour, per usable episode), and capacity planning. * Report throughput, quality, and cost to the executive team and adjust operations as research priorities shift. * Build a safe, well-run workplace for operators, collectors, and contributors.