Sr Manager, Data Factory Operation

The role

You will lead mid-end functions of Data Factory, overseeing centralized and decentralized data production pipelines. You will manage end-to-end execution of large-scale data collection to support training of Embodied AI models.

What you will do

• Direct the design, renovation, and construction of physical data collection sites.
• Manage the setup of diverse scenarios including retail, light manufacturing, and industrial production lines.
• Oversee the rental and maintenance of centralized collection robots and data processing hardware.
• Lead the global contributor network including onboarding, contracting, and registration of decentralized data collectors.
• Execute high-volume collection tasks managing 50+ devices across multiple shifts.
• Maintain and update the Data Collector User Manual.
• Design and enforce action standards and acceptance criteria for all collected data.
• Ensure technical compliance and quality rejection of unstable or occluded footage.
• Supervise the screening, filtering, and clipping of raw robot data and egocentric streams.
• Guarantee that all Visible Personally Identifiable Information is anonymized/blurred before delivery.

Required qualifications

• Bachelor’s or Master’s degree in Robotics, Computer Science, Mechanical Engineering, Industrial Engineering, Data Science, or a related technical field.
• 10+ years of experience in large-scale operations, robotics data collection, AI/ML data operations, manufacturing operations, operations management or aftersales.
• Deep understanding of data privacy laws (GDPR/CCPA) and PII handling requirements.
• Proven experience managing complex data production pipelines across centralized and distributed operational models.
• Strong understanding of Embodied AI (EAI), robotics systems, teleoperation workflows, sensor systems, and multimodal data collection processes.
• Hands-on experience designing and operating physical collection environments such as retail spaces, warehouses, manufacturing lines, or industrial simulation environments.
• Demonstrated ability to scale high-throughput operations involving large device fleets, multi-shift execution, and geographically distributed contributors.
• Experience developing and enforcing SOPs, operational standards, quality control processes, and acceptance criteria for large-scale data operations.
• Familiarity with robotics hardware and sensors, including RGB/RGB-D cameras, IMUs, LiDAR, VR teleoperation systems, and edge compute devices.
• Strong knowledge of data quality requirements, including video resolution standards, synchronization validation, calibration procedures, and dataset integrity checks.
• Experience with data annotation, preprocessing, clipping, filtering, and dataset acceptance workflows for AI/ML training pipelines.
• Understanding of privacy, compliance, and data governance requirements, including anonymization and handling of Personally Identifiable Information (PII).

Nice to have

• Familiarity with data quality control, VR Teleoperation, and multi-modal data formats (MCAP, HDF5).
• Experience working with humanoid robots, autonomous mobile robots (AMRs), or embodied AI model training datasets.
• Familiarity with synthetic data generation, simulation environments, or robotics benchmarking methodologies.
• Experience managing global contributor or crowdsourcing networks for AI data collection initiatives.
• Knowledge of manufacturing, warehouse automation, or industrial engineering workflows.
• Experience with cloud-based data infrastructure, data pipelines, or MLOps environments.
• PMP, Lean Six Sigma, or other operations/project management certifications

Benefits

• Healthcare + dental + vision benefits (Free for you/discounted for family)
• 401(k) options
• Casual dress code + relaxed work environment
• Culturally diverse, progressive atmosphere

About the company

Faraday Future (FF) is a California-based embodied artificial intelligence ecosystem company. The Company aims to disrupt the automotive and technology industries by creating user-centric, technology-first experiences.