Head of AI
Required skills
8+ years in ML/AI, with at least 3 years leading a team (hiring, managing, setting technical direction). Track record of shipping production ML systems on sensor data, geospatial data, or multi-modal data at scale. Experience setting AI/ML strategy for a product or business unit, not just executing someone else's roadmap. Hands-on technical depth: you can train models, design data pipelines, and evaluate architectural tradeoffs yourself. Experience with data-efficient learning approaches (active learning, semi-supervised methods, foundation model adaptation) in production. Led teams of 3+ ML/AI engineers and made successful senior technical hires. Strong communicator who can translate between technical AI/ML concepts and business/product strategy.
Preferred skills
Experience with LiDAR, point cloud data, or 3D perception. Background in autonomous vehicles, HD mapping, satellite imagery, or infrastructure/civil engineering domains. Experience building knowledge graphs or ontology-driven data architectures. Familiarity with geospatial databases (PostGIS, spatial indexing). Experience designing data architectures for agentic or LLM-driven access patterns. Background at Palantir, an AV company, or a geospatial intelligence organization. Experience at a startup or scaling an AI/ML function from zero.
Technologies
ML pipelines, sensor data, geospatial data, multi-modal data, data architecture, knowledge graph, AI/ML strategy, cloud pipelines, LiDAR, imagery, GPS data, geospatial insights, Infrastructure Intelligence Platform, PostGIS, spatial indexing.
Responsibilities
Interpret Cyvl's Infrastructure Intelligence vision and translate it into a concrete AI/ML technical strategy covering perception (imagery + LiDAR), knowledge representation, and data architecture. Be hands-on in the early months: set up the initial ML pipelines, make key architectural decisions, and validate technical approaches before you have a team. Hire and lead the AI/ML team, starting with a senior ML engineer and a senior knowledge graph architect as the first two roles. Own the full intelligence extraction pipeline: from raw sensor data to detections, geometric measurements, cross-modal representations, and a queryable knowledge graph. Work directly with the CEO and engineering leadership to align AI/ML investments with product priorities and customer needs.
Seniority
Senior
Domain
Transportation infrastructure, geospatial data, AI/ML, infrastructure intelligence, sensor data, government, public infrastructure
