Engineering Manager, Genai, Google Maps Immersive Navigation

Google Google · Big Tech · Mountain View, CA +1

Engineering Manager for GenAI in Google Maps Immersive Navigation. This role involves leading a team to build and scale a 3D navigation map using sensor data, large ML models, and AI techniques to create new geospatial data and user experiences. The manager will own the conversion of complex data into precise geometries, set team priorities, develop technical roadmaps, and guide system designs.

What you'd actually do

  1. Take end-to-end ownership of converting complex imagery, location, and sensor data into precise geometries to power Geo’s next generation navigation products. Translate ambiguous input data challenges into clear algorithmic, ML, GenAI formulations, brainstorming directly with product, UX, and engineering to define the optimal visual experience and iterate towards scalable solutions.
  2. Set and communicate team priorities that support the broader organization's goals. Align strategy, processes, and decision-making across teams.
  3. Set clear expectations with individuals based on their level and role, aligned with broader organizational goals. Meet regularly with individuals to discuss performance, development, feedback and coaching.
  4. Develop the long-term technical outlook and roadmap, meeting anticipated future requirements and infrastructure needs.
  5. Design, guide and vet system designs, and write product or system development code to solve ambiguous problems. Conduct code reviews and provide feedback ensuring best practices.

Skills

Required

  • software development
  • technical leadership
  • people management
  • ML design
  • ML infrastructure optimization
  • computer vision learning techniques
  • machine learning algorithms
  • generative AI
  • applied AI applications

Nice to have

  • Master's degree or PhD in Computer Science
  • Computer Vision
  • Reinforcement learning
  • ML infrastructure
  • research publications in top CV/ML conferences
  • modeling with TensorFlow, JAX

What the JD emphasized

  • extensive Machine Learning and Computer Vision experience
  • leading ML design
  • generative AI
  • applied AI applications

Other signals

  • leading ML design
  • generative AI
  • large ML models
  • AI techniques
  • 3D Immersive Navigation Experience