Strategic Project Lead

Shape the Future of AI At Labelbox, we're building the critical infrastructure that powers breakthrough AI models at leading research labs and enterprises. Since 2018, we've been pioneering data-centric approaches that are fundamental to AI development, and our work becomes even more essential as AI capabilities expand exponentially. About Labelbox We're the only company offering three integrated solutions for frontier AI development: Enterprise Platform & Tools : Advanced annotation tools, workflow automation, and quality control systems that enable teams to produce high-quality training data at scale Frontier Data Labeling Service : Specialized data labeling through Alignerr, leveraging subject matter experts for next-generation AI models Expert Marketplace : Connecting AI teams with highly skilled annotators and domain experts for flexible scaling Why Join Us High-Impact Environment : We operate like an early-stage startup, focusing on impact over process. You'll take on expanded responsibilities quickly, with career growth directly tied to your contributions. Technical Excellence : Work at the cutting edge of AI development, collaborating with industry leaders and shaping the future of artificial intelligence. Innovation at Speed : We celebrate those who take ownership, move fast, and deliver impact. Our environment rewards high agency and rapid execution. Continuous Growth : Every role requires continuous learning and evolution. You'll be surrounded by curious minds solving complex problems at the frontier of AI. Clear Ownership : You'll know exactly what you're responsible for and have the autonomy to execute. We empower people to drive results through clear ownership and metrics. Role Overview About the Role The Strategic Project Lead owns the day-to-day execution of our customer data projects. The SPL runs the project on the ground — keeping throughput, delivery, and quality on track from kickoff through steady-state to final delivery. As a rule, any project with a significant number of data trainers on it needs an SPL. SPLs own the operational core of a project: setting it up, bringing data trainers on, running it through its gates (calibration before scaling, staged ramp, delivery acceptance), tracking fulfillment and project margin, operating payment tiers, and keeping Airtable current as the system of record. By owning the running of the project, the SPL frees the Forward Deployed Engineer (FDE) to focus on higher-level technical and customer-facing work, and protects the Forward Deployed Researcher's (FDR) research time. The SPL sits at the intersection of operations, finance, and people coordination. They aren't bound to a single domain — they work across whatever projects need them. A key part of the role is keeping the FDE and FDR connected as a project kicks off, and orchestrating the data-trainer workforce through Pod Leads, who are central to the SPL's ability to deliver on complex projects. The SPL reports to the SPL Manager for craft and career, and on the ground takes delivery direction from the Deployment Lead on accounts that have one (the Deployment Lead owns the customer's delivery end-to-end and coordinates SPLs across its projects). It's a senior operating track: SPLs can grow into SPL Manager (managing other SPLs) or Deployment Lead (the customer-facing path), and from there toward a General Manager role. What You'll Do Run assigned projects day-to-day, owning throughput, delivery, and operational quality from kickoff through delivery; a SPL is staffed on any project with a meaningful number of data trainers. Run each project through its gates: calibrate before scaling, ramp in stages while quality holds, and meet acceptance criteria at delivery — so quality is enforced in flight, not discovered at the end. Set up projects and bring data trainers on using the platform tooling, configuring the right setup for different project types. Keep Airtable accurate as the system of record — tasks and status always current — owning tracking across internal projects (fulfillment, data-trainer tracking, sheets) and external projects (glide-path templates and margin tracking). Own project-level financials: track margin and fulfillment live, operate payment tiers, handle project billing/AR, and resolve data-trainer payment issues — flagging margin risk early and escalating margin-protecting changes to the comp structure to the Deployment Lead, who owns account-level margin. Keep the FDE and FDR connected as the project kicks off, so technical scoping and research inputs land in the work. Orchestrate the data-trainer workforce through Pod Leads — keeping trainers productive, paid, and organized, and using Pod-Lead first-line review as early quality signal — rather than managing hundreds of trainers directly. Identify delivery risks early, put mitigations in place, and escalate when throughput, quality, or timelines are at risk. Work fl