Software Engineer Iii, Ai/ml, Foundational Lanes

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

Software Engineer III, AI/ML role focused on improving the driving experience in Google Maps by leveraging AI/ML techniques for road and lane data extraction and construction of geometries. The role involves writing product/system development code, collaborating with peers, triaging issues, and implementing ML solutions, including model optimization and data processing.

What you'd actually do

  1. Write product or system development code.
  2. Collaborate with peers and stakeholders through design and code reviews to ensure best practices amongst available technologies (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
  3. Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.
  4. Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.
  5. Implement solutions in one or more specialized ML areas, utilize ML infrastructure, and contribute to model optimization and data processing.

Skills

Required

  • Java
  • Python
  • C++
  • end-to-end machine learning
  • model deployment
  • model evaluation
  • optimization
  • data processing
  • debugging
  • computer vision
  • reinforcement learning
  • sequential decision making
  • ML infrastructure
  • specialization in another ML field

Nice to have

  • Master's degree or PhD in Computer Science or related technical fields
  • data structures
  • algorithms
  • computational geometry
  • developing accessible technologies

What the JD emphasized

  • end-to-end machine learning (e.g., model deployment, model evaluation, optimization, data processing, debugging)
  • computer vision
  • reinforcement learning (e.g., sequential decision making)
  • ML infrastructure
  • specialization in another ML field

Other signals

  • Leveraging AI/ML techniques to extract road and lane data
  • geometric algorithms (including GenAI) to construct consistent and smooth road and lane shapes
  • Implement solutions in one or more specialized ML areas, utilize ML infrastructure, and contribute to model optimization and data processing.