Strategic Project Lead – Multimodal AI

This is a fully remote position, open to applicants in United Kingdom.

📋 Description

• Spearhead AI post-training initiatives that assist organizations in creating and enhancing frontier models through high-caliber data programs.

• Take ownership of comprehensive project delivery, including scope, timelines, budgets, staffing, and risk management.

• Direct client interactions, status updates, planning meetings, and escalation processes.

• Convert technical and client specifications into data collection workflows, annotation guidelines, tools, and quality benchmarks.

• Establish quality metrics and acceptance criteria for multimodal data and annotation results.

• Oversee delivery quality, address data-related challenges, and clarify ambiguous client requirements.

• Provide guidance on project viability, collection techniques, annotation strategies, and tooling.

• Create reusable SOPs, guidelines, and quality assurance frameworks.

• Mentor Operations Specialists and assist in project scoping, pilot initiatives, and developing multimodal AI capabilities.

• Collaborate with clients and internal teams to convert AI research needs into dependable datasets and quantifiable outcomes.

⛳️ Requirements

• 1–2+ years of experience in AI data operations, project coordination, or delivery, preferably within a GenAI or frontier AI setting.

• Knowledge of at least one multimodal data workflow that includes images, video, 3D data, sensors, or robotics.

• Proven experience in coordinating projects or workstreams, managing stakeholders, and engaging with clients.

• Comprehension of data quality, annotation workflows, and quality assurance techniques.

• Capability to translate project needs into well-defined data collection workflows, annotation guidelines, and quality benchmarks.

• Strong problem-solving abilities and proficiency in managing multiple priorities in a dynamic environment.

• Keen interest in the latest AI advancements, 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.

• Background in autonomous systems, spatial AI, or embodied AI.

• Bilingual skills, especially in German or a Nordic language, are a plus.

🏝️ Benefits

• Permanent - Regular Full-time employment.

• Flexible work arrangements.

• Access to tools, resources, and development opportunities.

• Culture of innovation, collaboration, and excellence.

• Opportunity to tackle complex AI challenges across various industries and regions.

• Mentoring and capability-building opportunities.