Strategic Project Lead - Multimodal AI (United States)

The Strategic Project Lead – Multimodal AI supports frontier AI development through complex, high-quality data programs for leading AI companies. We're looking for someone with experience in multimodal AI data, such as image, video, 3D, sensor, or robotics-related workflows. You'll lead projects that turn complex real-world data into reliable training and evaluation resources. Combining project management with hands-on domain knowledge, you'll partner with clients and internal teams to design workflows, maintain quality, and solve challenging data delivery problems in a rapidly evolving AI market.

Responsibilities

Own end-to-end project delivery across scope, timelines, budgets, staffing, and risks; Lead client communication, status reporting, planning sessions, and escalations; Translate technical and client requirements into data collection workflows, annotation guidelines, tooling, and quality standards; Define quality metrics and acceptance criteria for multimodal data and annotation outputs; Monitor delivery quality, troubleshoot data issues, and resolve ambiguous requirements with clients; Advise on project feasibility, collection methods, annotation approaches, and tooling based on your domain expertise; Build reusable SOPs, guidelines, and QA frameworks to support consistent delivery; Mentor Operations Specialists and contribute to project scoping, pilots, and emerging multimodal AI capabilities

Requirements

1–2+ years of experience in AI data operations, project coordination, or delivery, ideally in a GenAI or frontier AI environment; Familiarity with at least one multimodal data workflow involving images, video, 3D data, sensors, or robotics; Experience coordinating projects or workstreams, managing stakeholders, and communicating with clients; Understanding of data quality, annotation workflows, and quality assurance methods; Ability to translate project requirements into clear data collection workflows, annotation guidelines, and quality standards; Strong problem-solving skills and the ability to manage multiple priorities in a fast-moving environment; Interest in current AI developments, including multimodal models, spatial AI, or embodied AI

Nice to have

Experience with image or video annotation, 3D data, point clouds, or sensor data; Familiarity with robotics data collection or real-world perception workflows; Exposure to 2D or 3D labeling, segmentation, tracking, or structured annotation tasks; Experience with autonomous systems, spatial AI, or embodied AI; Bilingual capabilities, particularly German or a Nordic language

Benefits

Flexibility to deliver in a way that works for you and your team; Tools, resources, and development opportunities to build your capability over time