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Waymo

2027 Summer Intern, BS, Software Engineer, Driver Refinement Foundations

Mountain View, CA, USAinternshipinternAdded today

About this role

Waymo seeks a software engineering intern to develop C++ autolabeler tools for extracting and validating useful driving events from autonomous vehicle data. You'll work on the Reasoning Platform team, experimenting with labeling approaches and evaluating data quality while gaining hands-on experience in autonomous driving technology.

What you'll do

  • Develop and optimize C++ autolabeler code to extract meaningful events from driving datasets
  • Create ground truth labels and assess autolabeler performance and quality metrics
  • Test and experiment with different labeling methodologies, documenting results
  • Design and implement metrics to evaluate system performance
  • Collaborate with team members on code reviews and technical discussions
  • Work on software testing including unit, integration, and regression testing

What they're looking for

  • C++
  • Algorithms and data structures
  • Software testing (unit, integration, regression)
  • Data analysis and metrics design
  • Version control systems
  • Linux development environment
  • Team collaboration and communication
  • Autonomous driving concepts

Benefits

  • Competitive hourly compensation with housing/relocation bonus if applicable
  • Medical, dental, and vision insurance
  • Free meals (breakfast, lunch, dinner, snacks)
  • Free Google shuttle access
  • Onsite gym
  • Intern networking events and community
Apply on the employer's site

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Waymo

Waymo develops autonomous driving technology and vehicles, building the AI systems, simulation platforms, and infrastructure that power the Waymo Driver. The company is hiring for ML infrastructure engineers, platform engineers, labeling system developers, backend software engineers, and automotive systems engineers to scale its autonomous driving capabilities.

Website
waymo.com
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Likely interview questions

  • Walk us through a complex C++ project you've built and the challenges you overcame with performance optimization.
  • How would you design metrics to evaluate the quality of an autolabeler system?