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Location
Hybrid (Foster City, United States)
Seniority
Intern
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Employment
Internship

Confirmed on the employer's own hiring board on Nov 13, 2026. First seen by Alion on Nov 12, 2026. Zoox scores B on the Alion truth index.

Overview
Company
Impact
Profile match
Zoox is an American autonomous vehicle company founded in 2014 that designs a purpose-built robotaxi rather than retrofitting an existing car. Its vehicle has no steering wheel or driver position, seats four passengers facing each other, drives equally well in either direction and was developed alongside the sensors, compute and software that operate it, which required the company to certify the design under its own self-certification of federal motor vehicle safety standards. Amazon acquired the company in 2020 and it has since begun public robotaxi service in Las Vegas and San Francisco while testing in several other American cities.

About Our Internship Program

Zoox’s internship program offers hands-on experience with cutting-edge technology, mentorship from some of the industry's brightest minds, and the opportunity to make meaningful contributions to real projects. We seek interns who demonstrate strong academic performance, engagement beyond the classroom, intellectual curiosity, and a genuine interest in Zoox's mission to create autonomous mobility from the ground up.

Job Description

As an intern in the Quantitative Risk Assessment (QRA)team within System Design & Mission Assurance, you will apply rigorous statistical methods and machine learning techniques to quantify safety and risk across our autonomous driving systems. You will work with complex, real-world fleet and simulation datasets to model rare safety events, establish statistical baselines, and develop metrics that validate the safety and mission assurance of our purpose-built robotaxi.

In this Role, You Will…

  • Formulate and build statistical and machine learning modelsto evaluate system performance and analyze rare, high-consequence safety events.
  • Process and analyze large-scale datasetsusing SQL, Python, or distributed data frameworks (Spark/Databricks) to extract actionable insights on vehicle behavior and operational risk.
  • Apply advanced statistical methods(e.g., Poisson processes, GLMs, Bayesian inference, point process models, or spatial-temporal modeling) to evaluate safety-critical metrics.
  • Collaborate with systems engineers and safety leadsto translate complex quantitative models into rigorous mission assurance decisions.

Internship Requirements

  • Currently pursuing a Master's or Ph.D. in Statistics, Data Science, Machine Learning, Computer Science, or a related quantitative engineering/scientific discipline.
  • Enrolled in good academic standing at an accredited college or university throughout the internship.
  • Expected to graduate between Fall 2027 and Summer 2028.
  • Able to commit to a full-time, 12-week internship beginning in May/June 2027.
  • Ability to relocate to the Bay Area, California, for the duration of the internship.
  • Interns at Zoox may not use any proprietary information they are working on as part of their thesis, any published work with their university, or to be distributed to anyone outside of Zoox.

Qualifications

  • Statistical Foundations:Deep understanding of probability theory, regression, Generalized Linear Models (GLMs), hypothesis testing, and Bayesian methods. Experience or coursework in spatial statistics, space-time models, point process models, or causal inference.
  • Machine Learning & Modeling:Strong fundamentals in statistical modeling and ML (supervised and unsupervised learning, model validation, and metric evaluation).
  • Data Manipulation & Querying:Proficiency with basic-to-intermediate SQL and Python for data querying, data cleaning, and statistical modeling (or alternative data packages such as Spark, dplyr, or R).
  • Communication & Problem Solving:Demonstrated ability to break down ambiguous operational or system questions into structured statistical problems and clearly communicate complex quantitative findings to technical stakeholders.

Bonus Qualifications

  • Large-Scale Data Processing:Experience querying, pipeline-building, and modeling massive datasets using Spark, Databricks, or cloud platforms.
  • Rare-Event Modeling & Domain Experience:Familiarity with autonomous vehicles, transportation network companies (TNCs), quantitative safety/risk modeling, or fraud/rare-event detection.
  • AI-Assisted Workflow & Tooling:Experience utilizing AI-assisted data analysis, modern coding agents, or LLM-driven research workflows to accelerate data exploration and model development.
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