Key Responsibilities

• Support Data Strategy Execution: Assist in translating research roadmaps into actionable data sourcing plans, helping to track and fill technical data gaps identified by algorithm leaders.
• Coordinate Vendor & Partner Relations: Serve as a primary operational point of contact for external data vendors and open-source communities—managing onboarding, tracking delivery timelines, and ensuring adherence to service level agreements.
• Streamline Data Evaluation Workflows Manage the internal routing of external datasets for technical review, tracking quality benchmarks and utility metrics to accelerate research team readiness
• Maintain Data Pipelines: Facilitate seamless dataset onboarding by accurately documenting external data specifications and tracking their successful integration into internal pre-training pipelines.
• Assist with Data Governance Tracking: Work closely with Legal, Privacy, and Security teams to document data provenance, track compliance metrics (including CCPA/CPRA), and maintain clear logs of licensing terms and usage rights.
• Drive Operational Efficiency: Maintain internal dashboards, pipeline tracking tools, and documentation to maximize research velocity and ensure data operations run smoothly.

Qualifications

• Operational Background: Prior experience in high-leverage or fast-paced technical environments such as Technical Project Management, AI/Tech Operations, Data Licensing coordination, or business analysis.
• Detail-Oriented Project Management: Proven ability to manage multiple moving parts, keep vendor pipelines organized, and handle data tracking without losing oversight of details.
• Exposure to AI/ML Workflows: A foundational understanding of (or strong interest in) AI/ML systems, data generation pipelines, or human-in-the-loop (RLHF) operations.
• Clear Communicator: Strong verbal and written communication skills, with the ability to clearly pass requirements between technical teams, legal teams, and external partners.