2027 Summer Intern, MS/PhD, Machine Learning Engineer

Waymo
San Francisco, CA
Career-pivot friendly

Who this role is best for

Strong fit for candidates with advanced degrees in ML or CS who can train and debug large-scale transformer models on TPUs, and who are comfortable with high-traffic codebases and cross-team collaboration in the autonomous driving domain.

Best fit for

  • Candidates with advanced degrees in ML or CS and experience in training large transformer models on TPUs
    — “Train and fine-tune a large multi-task transformer over driving-log sequences, in JAX/Flax on TPUs”
  • Individuals who can design rigorous evaluations and build evaluation pipelines for autonomous driving systems
    — “Design and run rigorous offline and end-to-end evaluations - PR-AUC, calibration quality, and metric sensitivity on real hillclimbing A/B runs”
  • Candidates who can write production-quality code and collaborate with multiple stakeholders across teams
    — “Land production-quality code in a shared, high-traffic codebase, and communicate results through a design doc, team deep dives, and a final intern presentation, partnering with UEM Core, Data Science, and release-eval stakeholders”

Things to consider

  • Returning to academic program after the internship is a requirement, not just a preference
    — “Currently enrolled in an PhD or MS program in Computer Science, Machine Learning or a related field, returning to the program after the internship”
  • The role requires a hybrid onsite arrangement, which may involve travel or relocation
    — “This will be a hybrid onsite internship position”

How to stand out

  • Highlight experience with JAX/Flax and TPU-based distributed training on your resume
    — “training and evaluating deep learning models in a modern framework (JAX, PyTorch or TensorFlow)”
  • Emphasize your ability to build and debug data pipelines for large-scale ML projects
    — “including building data pipelines, choosing losses, and debugging training runs”
  • Showcase your track record in publishing papers in top-tier AI/ML conferences
    — “Authorship of published papers in top-tier AI/ML, data mining, or computer vision conferences”
  • Demonstrate familiarity with autonomous driving or robotics in your application materials
    — “Familiarity with autonomous driving, robotics, or simulation”
  • Demonstrate your ability to partner with multiple stakeholders and present results effectively
    — “communicate results through a design doc, team deep dives, and a final intern presentation, partnering with UEM Core, Data Science, and release-eval stakeholders”
Pace · Fast PacedCollaboration · HighAutonomy · MediumDecision Impact · Team

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

What success looks like

  • Train and fine-tune a large multi-task transformer over driving-log sequences
  • Design and run rigorous offline and end-to-end evaluations
  • Land production-quality code in a shared, high-traffic codebase
Typical background
MS/PhD in Computer Science, Machine Learning or a related field

Skills & requirements

Required

Machine LearningDeep LearningData PipelinesTraining ModelsEvaluation MetricsProgramming SkillsAutonomous Driving

Preferred

Published Papers In Top-tier Ai/ml ConferencesExperience With Transformer And Sequence ModelsDistributed Training On Tpus Or GpusLarge-scale Data Processing

Stack & domain

Training And Fine-tuning Large Multi-task TransformersDriving-log Sequences AnalysisJax/flaxTpusFine-tuning StrategiesTraining Data MixturesLossesEvaluation Quality ImprovementHillclimbing WorkflowPr-aucCalibration QualityMetric SensitivityReal Hillclimbing A/B RunsProduction-quality CodeDesign DocTeam Deep DivesFinal Intern PresentationUEM CoreData ScienceRelease-eval StakeholdersDeep Learning Models Training And EvaluationModern FrameworkData PipelinesTraining Runs DebuggingC++/pythonML FundamentalsPrecision/recall Trade-offsClass ImbalanceEvaluation Metric SelectionRigorous Experiment DesignTeamworkPresentationCommunicationProblem-solvingMachine LearningAutonomous DrivingAI

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. 

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:

Train and fine-tune a large multi-task transformer over driving-log sequences, in JAX/Flax on TPUs - iterating on fine-tuning strategies, training data mixtures, and losses to improve evaluation quality for the hillclimbing workflow

Design and run rigorous offline and end-to-end evaluations - PR-AUC, calibration quality, and metric sensitivity on real hillclimbing A/B runs - and build the dataset and evaluation pipelines needed to produce them

Land production-quality code in a shared, high-traffic codebase, and communicate results through a design doc, team deep dives, and a final intern presentation, partnering with UEM Core, Data Science, and release-eval stakeholders

You have:

Currently enrolled in an PhD or MS program in Computer Science, Machine Learning or a related field, returning to the program after the internship

Hands-on experience training and evaluating deep learning models in a modern framework (JAX, PyTorch or TensorFlow), including building data pipelines, choosing losses, and debugging training runs

Strong programming skills in C++/Python, plus a solid grounding in ML fundamentals: precision/recall trade-offs, class imbalance, evaluation metric selection, and rigorous experiment design

We prefer:

Authorship of published papers in top-tier AI/ML, data mining, or computer vision conferences (e.g., NeurIPS, ICML, ICLR, KDD, CVPR, CoRL, SIGMOD, VLDB, ACL)

Research or applied experience with transformer and sequence models, multi-task learning, transfer learning or domain adaptation, and parameter-efficient fine-tuning of large pretrained models

Experience with JAX/Flax, distributed training on TPUs or GPUs, and large-scale data processing (MapReduce-style pipelines, SQL) for building training and evaluation datasets

Familiarity with autonomous driving, robotics, or simulation; and/or with probability calibration, uncertainty quantification, importance sampling, active learning, or rare-event and imbalanced-data modeling

General Perks

Help solve challenging problems with a direct impact on the company

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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