Data Operations Team Leader

Description:

Prisma-Photonics is a rapidly growing startup company, developing the next-generation smart-infrastructure solution based on novel fiber-sensing technology (smart roads, smart cities, perimeters, and grid monitoring, etc.). The company offers an award-winning disruptive solution; a “sensor free” approach to smart infrastructure. The company is VC backed and in the revenues stage. 

Combining pioneering technology in optical fiber sensing with state-of-the-art machine learning, we help prevent environmental disasters, protect human lives, and keep critical energy and transportation backbones running smoothly.

We are seeking our Data Operations Team Leader!

This person will oversee a team of data operations specialists responsible for labeling data for machine learning and AI projects.

This role involves managing day-to-day operations, ensuring annotation quality and accuracy, developing guidelines, and collaborating with cross-functional teams to meet project deadlines and objectives.

• Manage the end-to-end data workflow, from incoming data through annotation delivery to the ML teams, including overseeing data upload processes and ensuring data availability.
• Manage database operations and ensure the integrity and availability of annotation data.
• Become a Subject Matter Expert in our data and actively participate in hands-on annotation projects.
• Create and maintain onboarding materials, annotation guidelines, and operational documentation to support knowledge sharing and consistent annotation practices.
• Lead a team of Data Operations Specialists by managing task assignments, scheduling, and day-to-day execution. Provide the tools and processes needed for efficient work, ensure high annotation quality in collaboration with the ML teams, and continuously improve workflow efficiency
• Own the annotation platform, driving bug fixes, feature development, and workflow improvements using Python and GenAI tools.
• Develop and maintain operational dashboards and real-time performance metrics to monitor team efficiency, quality, and output.
• Collaborate closely with data scientists, machine learning engineers, and product managers to understand annotation requirements and project goals. Coordinate cross-functional communication, monitor operational KPIs, and oversee daily operations to keep projects on track and ensure adherence to shifting schedules.