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Waymo

2027 Summer Intern, PhD, Quantitative Software Engineer

Mountain View, California, United States | San Francisco, California, United States$176.4k–$176.4kinternshipinternAdded today

About this role

Waymo seeks a PhD student in Computer Science or related field to conduct exploratory research and develop software for autonomous driving technology. You'll work on statistical evaluation of new theories, present findings to teams, and implement engineering solutions that contribute to the Waymo Driver's perception and decision-making capabilities.

What you'll do

  • Conduct exploratory research and statistical evaluation of new theories in autonomous driving
  • Present research findings and analysis to focus groups and internal teams
  • Design and implement software solutions for autonomous vehicle systems
  • Collaborate with hardware and systems engineers on robotics and perception challenges
  • Apply machine learning techniques to autonomous driving problems

What they're looking for

  • Python programming
  • Statistical analysis and evaluation
  • Machine learning fundamentals
  • Software engineering design and implementation
  • Research methodology
  • Technical communication and presentation
  • Robotics or autonomous systems knowledge
  • Data analysis

Benefits

  • Hybrid onsite internship at Mountain View or San Francisco locations
  • Partnership with industry leaders on impactful projects
  • Generous benefits program participation
  • Two-way learning and skill development opportunities
  • Direct exposure to Level 4 autonomous driving technology
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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 research project where you evaluated a novel theory—how did you design your statistical evaluation?
  • Describe your experience with machine learning. What specific applications or algorithms have you worked with?