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.

Your Impact

• 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.

What You Bring

• 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.

About Appen

Appen has been a leader in AI training data for over 30 years. We specialise in human generated data to train, fine tune, and evaluate models across generative AI, large language models, computer vision, and speech recognition. Our AI assisted data annotation platform and global crowd of more than 1 million contributors in over 200 countries support model pre training, supervised fine tuning, evaluation and benchmarking, safety and red teaming, and multilingual global expansion.