Sr Manager, Data Factory Operation

Faraday Future•El Segundo, CA

11d•$180,000 - $200,000

About The Position

Faraday Future (FF) is a California-based embodied artificial intelligence ecosystem company, leveraging the latest technologies and world’s best talent to realize exciting new possibilities in mobility and robotics. We’re producing user-centric, technology-first vehicles and robots to establish new paradigms in human-AI interaction. We’re not just seeking to change how our cars and robots work – we’re seeking to change the way we drive and interact with machines. At FF, we’re creating something new, something connected, and something with a true global impact. Founded in 2014, the Company’s mission is to disrupt the automotive and technology industries by creating user-centric, technology-first experiences. The Company, together with its controlled subsidiaries, operates across multiple technology-driven areas, including AI electric vehicles, robotics, and its crypto business (AIXC), all under its upgraded Global EAI Industry Bridge Strategy, marking the beginning of a new chapter in AI mobility and Web3 integration. The Company aims to leverage the latest technologies and world’s best talent to realize exciting new possibilities across all of these lines. Faraday Future’s automotive business exemplifies its vision for luxury, innovation, and performance, while its FX strategy aims to introduce mass production models equipped with state-of-the-art luxury technology derived from the FF brand, targeted towards a broader market with middle-to-low price range offerings. FF is committed to redefining mobility through AI innovation. Join us in shaping the future of intelligent transportation and technology by creating something new, something connected, and something with a true global impact. As the Senior Manager of Data Factory Operation, you will lead the mid-end functions of Data Factory, overseeing both centralized and decentralized data production pipelines. You are responsible for the end-to-end execution of large-scale data collection—ranging from environment design to real-world robot data submission—to support the training of Embodied AI (EAI) models.

Requirements

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).
Proven ability to manage vendors, contractors, equipment rentals, and operational budgets in fast-paced environments.
Strong project management and cross-functional coordination skills, with the ability to align engineering, operations, and client delivery teams.
Excellent analytical and problem-solving capabilities with a data-driven approach to operational optimization and continuous improvement.
Experience supporting enterprise or technical clients, including troubleshooting, remote operational support, and translating client feedback into process improvements.
Exceptional written and verbal communication skills, including documentation, reporting, and stakeholder management.
Willingness to travel domestically and internationally to support site launches, client engagements, and operational execution as needed.

Nice To Haves

Technical Knowledge: 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 are a plus.

Responsibilities

Site Infrastructure & Layout Design (Centralized Operations)
On-demand Environment Construction: Direct the design, renovation, and construction of physical data collection sites based on specific project needs.
Scenario Layout: Manage the setup of diverse scenarios, including retail (supermarket shelves), light manufacturing (electronics assembly), and industrial production lines (conveyor belts).
Resource Management: Oversee the rental and maintenance of centralized collection robots and data processing hardware.
Large-Scale Operational Execution
Workforce Management: Lead the global contributor network, including the onboarding, contracting, and registration of decentralized data collectors.
Throughput Management: Execute high-volume collection tasks, such as the 20,000-hour industrial luggage factory requirement, managing 50+ devices across multiple shifts .
SOP Development: Maintain and update the "Data Collector User Manual," covering VR teleoperation instructions and sensor calibration protocols.
Standards, Quality & Acceptance
Standardization: Design and enforce action standards and acceptance criteria for all collected data.
Data Integrity: Ensure technical compliance (1080p+, 30FPS+, FOV 130+, IMU sync) and quality rejection of unstable or occluded footage .
Preliminary Acceptance: Supervise the screening, filtering, and clipping of raw robot data and egocentric streams before submission to clients.
Compliance & Privacy: Guarantee that all Visible Personally Identifiable Information (PII) is anonymized/blurred before delivery .
Client Support & Technical Liaison
Remote & On-site Support: Provide technical and operational support for client-specific teleoperation and data inquiry needs.
Feedback Loops: Continuously optimize data collection actions and execution protocols based on client feedback and model performance metrics.