Data Collection Operations Technician

We are looking for a hands-on, detail-oriented Data Capture Operations Technician to serve as our on-site operator at our Philadelphia factory data capture facility. You will be responsible for managing the day-to-day operations of our multi-camera data capture system, ensuring continuous high-quality data flows from dozens of cameras to our cloud storage infrastructure. This is a critical role at the intersection of hardware operations, basic networking, and AI data pipelines., Camera System Management

• Set up, configure, calibrate, and maintain a fleet of IP cameras (Reolink) and head-mounted egocentric capture devices (Raspberry Pi-based and/or GoPro)

• Distribute and collect head-mounted camera rigs to/from factory workers at shift changes

• Monitor camera health, video quality, and streaming status throughout shifts; troubleshoot issues in real time

• Manage charging stations, power banks, SD cards, and other capture hardware inventory Data Pipeline Operations

• Monitor the automated data pipeline: camera streams * local capture server * IBM Cloud Object Storage

• Verify data integrity, completeness, and upload status daily; flag and resolve pipeline failures

• Perform basic troubleshooting on Raspberry Pi capture servers, networking equipment, and FTP/watchdog scripts

• Maintain organized data logs including camera IDs, timestamps, worker assignments, and capture session metadata On-Site Coordination

• Serve as the primary DreamVu point of contact at the factory facility

• Coordinate with factory management to ensure smooth integration of capture operations with daily workflows

• Brief and assist factory workers on proper use of head-mounted capture devices

• Maintain a clean, organized, and safe equipment staging area Reporting & Communication

• Provide daily status updates to the DreamVu engineering and research team (via Slack)

• Document any hardware issues, environmental factors, or process improvements

• Track capture hours, data volumes, and camera uptime metrics

• High school diploma or equivalent; Associate's degree or technical certification preferred
• Comfort working with hardware: cameras, cables, SD cards, USB devices, power supplies, mounting equipment
• Basic computer literacy including command-line/terminal usage (Linux a plus)
• Basic understanding of WiFi networking (connecting devices to a network, checking IP addresses, signal troubleshooting)
• Reliability and punctuality - this role requires on-site presence during factory shift hours
• Strong attention to detail and ability to follow documented procedures
• Good communication skills; comfortable interacting with factory floor workers and remote engineering team
• Ability to stand, walk, and carry light equipment (up to 15 lbs) throughout a shift

Preferred Qualifications

• Experience with IP cameras, security camera systems, or AV equipment setup
• Familiarity with Raspberry Pi, Arduino, or similar single-board computers
• Experience with basic scripting (Python or Bash) or willingness to learn
• Previous experience in warehouse, manufacturing, or factory environments
• Interest in AI, robotics, or computer vision (no prior expertise required)
• Experience with cloud storage platforms (AWS S3, IBM Cloud, Google Cloud)

• Ground-floor opportunity at a venture-backed AI startup with significant equity upside
• Hands-on role directly contributing to cutting-edge robotics and AI research
• Mentorship and skill development in AI data infrastructure, an in-demand and rapidly growing field
• Collaborative, fast-paced startup culture with a small, high-impact team
• Medical and dental benefits

DreamVu is a Physical AI data infrastructure startup building the training data pipelines that will power the next generation of embodied AI and humanoid robotics. Just as large language models were unlocked by internet-scale text data, we believe the same breakthrough in robotics requires massive, high-quality, real-world multimodal datasets. Our proprietary omnidirectional 3D capture technology and enriched data pipelines serve leading foundation model teams across the industry.