AI ML Engineer

What's the role?

About the RoleAI & Analytics Infrastructure brings together Analytics Engineering, AI Infrastructure, Responsible AI, and domain AI teams (e.g., AI for Mapmaking) to provide reusable building blocks agents, tools, data access, semantics that run on a shared infrastructure and control layer (agentic frameworks, agentic identity, guardrails). This unlocks fast, scalable, and safe AI adoption, and lets domain teams focus on innovation rather than re-building operational plumbing each time.

This role builds the geospatial-specific building blocks themselves embeddings, retrieval, and data-access components that power systems . Without this role, that build capacity falls to senior/lead engineers who should be focused on architecture rather than day-to-day implementation and the pace at which new geospatial capabilities reach the shared layer slows down. A Geo AI Engineer II supplies that build capacity now, while developing the geospatial-AI depth this central function will keep needing as more domain teams plug into the shared layer.

What You'll Do

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• Build reusable geospatial AI building blocks embeddings, similarity search, and retrieval components that other domain teams consume rather than rebuild.

• Contribute to production agentic pipelines , implementing and improving detection, validation, and data-handling components that process real map and imagery data.

• Prepare and engineer geospatial data (imagery, map data, sensor/traffic signals) as AI feature-engineering input framed as an AI capability, not classic GIS infrastructure.