2027 Summer Intern, MS/PhD, Machine Learning, Driver Refinement Foundations

Waymo
Mountain View, CA
On-siteCareer-pivot friendly

Who this role is best for

Aimed at graduate-level researchers or engineers with ML expertise who can work in a hybrid onsite environment and contribute to foundational systems for autonomous driving behavior refinement.

Best fit for

  • Graduate-level ML researchers or engineers with strong data-driven problem-solving skills
    — “currently enrolled in a graduate program (Master's or PhD) in Computer Science or a related technical field”
  • Candidates experienced in model evaluation and optimization techniques
    — “Experience in model evaluation and developing metrics”
  • Individuals with a background in deep learning frameworks like Jax/PyTorch
    — “Good understanding of Jax/Pytorch”

Things to consider

  • Hybrid onsite work is expected, with a potential for in-office days
    — “This will be a hybrid onsite internship position”
  • PhD candidates may receive higher compensation than Master's candidates
    — “Hourly Masters Pay$70—$70 USD”

How to stand out

  • Highlight experience in building or refining evaluation metrics for complex models
    — “Design and implement Evaluation metrics and iterate on improvements”
  • Demonstrate familiarity with large language models and their application in decision-making
    — “Leverage large language models and world foundation models for reasoning, decision making and multi-modality generation”
  • Showcase projects involving reinforcement learning and reward modeling
    — “Optimize Multimodal generative models using RLFT. Explore Reward modeling”
Pace · Fast PacedCollaboration · HighAutonomy · MediumDecision Impact · Company

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • improved driving behavior
  • optimized generative models
  • enhanced evaluation metrics
Typical background
computer sciencemachine learning

Skills & requirements

Required

PythonC++JaxPyTorchMachine Learning

Preferred

SQLReinforcement Learning

Stack & domain

PythonC++JaxPyTorchRLFTProblem-solvingTeamworkLeadershipCuriosityMachine LearningAutonomous DrivingData Analysis

About the role

Original posting from Waymo

Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states.

Software Engineering builds the brains of Waymo's fully autonomous driving technology. Our software allows the Waymo Driver to perceive the world around it, make the right decision for every situation, and deliver people safely to their destinations. We think deeply and solve complex technical challenges in areas like robotics, perception, decision-making and deep learning, while collaborating with hardware and systems engineers. If you’re a software engineer or researcher who’s curious and passionate about Level 4 autonomous driving, we'd like to meet you. 

The subteam for this role will be:

Driver Refinement foundations - The team is accountable for providing the common, consistent framework (and enabling expertise) for post-training and heuristic hill climbing across the entire Planner organization. We build fundamental platforms, including the Data Flywheel and the Reasoning platform, to assist Waymo engineers in delivering driving behavior improvements using data-driven and heuristic methods.

Waymo interns partner with leaders in the industry on projects that create impact to the company. We believe learning is a two-way street: applying your knowledge while providing you with opportunities to expand your skill-set. Interns are an important part of our culture and our recruiting pipeline. Join us at Waymo for a fun and rewarding internship!

You will:

Mine and curate dataset samples from large corpus of driving data

Leverage large language models and world foundation models for reasoning, decision making and multi-modality generation

Optimize Multimodal generative models using RLFT. Explore Reward modeling

Design and implement Evaluation metrics and iterate on improvements

You have:

Currently enrolled in a graduate program (Master's or PhD) in Computer Science or a related technical field

You have strong problem solving and programming skills in Python and/or C++

Good understanding of Jax/Pytorch

Experience in model evaluation and developing metrics

Experience developing models

We prefer:

Some understanding of SQL is preferred, not required

Previous Internship experience

PhD preferred

General Perks

Competitive compensation packages with a housing/relocation bonus (if applicable)

Medical, dental, and vision insurance

Fun intern events and networking opportunities

Onsite Perks

Free breakfast, lunch, dinner, and snacks 

Free access to Google shuttles

Onsite gym

Note: This will be a hybrid onsite internship position. We will accept resumes on a rolling basis until the role is filled. To be in consideration for multiple roles, you will need to apply to each one individually - please apply to the top 3 roles you are interested in.

The expected hourly rate for this full-time position is listed below. Interns are also eligible to participate in the Company’s generous benefits programs, subject to eligibility requirements.Hourly Masters Pay$70—$70 USDThe expected hourly rate for this full-time position is listed below. Interns are also eligible to participate in the Company’s generous benefits programs, subject to eligibility requirements.Hourly PhD Pay$85—$85 USD

Source: Waymo careers

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