Strategic Project Lead - Multimodal AI (London)

About the Role

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. 

• 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. 

• 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. 

• 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.