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Precedente Avanti

Reliability Data Intern

Zoox · Foster City, Stati Uniti d'America · Hybrid

  • Ufficio in Foster City
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Zoox is transforming mobility with fully autonomous, electric vehicles designed from the ground up for a driverless future. Our mission is to make transportation safer, more sustainable, and accessible to everyone. At Zoox, innovation, collaboration, and a bold vision for the future drive everything we do.

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.

This internship opportunity is within the Hardware Reliability team, which focuses on building the data infrastructure and analytical capabilities that ensure our autonomous vehicle fleet operates safely and reliably. Interns on this team will have the chance to work on developing data pipelines, performing reliability analyses, and creating visualization tools that directly support Zoox's mission to bring autonomous urban mobility to reality, gaining valuable experience and insight into how data science drives hardware reliability decisions in cutting-edge autonomous vehicle technology.

Program Requirements
  • Currently pursuing a B.S., M.S., or other advanced degree in Engineering, Statistics, Applied Mathematics, Data Science, or related field
  • Plan to return to school after completing the internship.
  • Maintain good academic standing.
  • Available to commit to a 12-week internship beginning in May or June 2026.
  • At least one prior industry internship, co-op, or relevant project experience.
  • Willing and able to relocate to the Bay Area, California, for the duration of the internship.
  • Interns may not use proprietary Zoox information in university theses, publications, or share it outside of Zoox.
Qualifications
  • Coursework or project experience in data analysis and visualization techniques
  • Working knowledge of SQL and database concepts
  • Working knowledge of Python and applicable packages such as Pandas, Numpy and Scipy
  • Familiarity with version control systems (Git)
  • Strong communication and collaboration skills
  • Ability to work on-site in Foster City, CA
Bonus Qualifications
  • Coursework or experience in reliability engineering or statistical inference techniques
  • Experience with Spark or large-scale data analysis
  • Familiarity with Databricks
  • Experience mining Jira or similar project management tools for data
  • Automotive or hardware reliability interest/experience
  • Understanding of failure mechanisms and damage models
  • Exposure to prognostic health monitoring concepts
  • Machine learning experience (supervised/unsupervised learning, model training and evaluation)


Compensation:
The monthly salary range for this position is $6,500 to $7,500. Compensation will vary based on geographic location and level of education. Additional benefits may include medical insurance, and a housing stipend (relocation assistance will be offered based on eligibility).

About Zoox
Zoox is developing the first ground-up, fully autonomous vehicle fleet and the supporting ecosystem required to bring this technology to market. Sitting at the intersection of robotics, machine learning, and design, Zoox aims to provide the next generation of mobility-as-a-service in urban environments. We’re looking for top talent that shares our passion and wants to be part of a fast-moving and highly execution-oriented team.


Accommodations
If you need an accommodation to participate in the application or interview process please reach out to [email protected] or your assigned recruiter.

A Final Note:
You do not need to match every listed expectation to apply for this position. Here at Zoox, we know that diverse perspectives foster the innovation we need to be successful, and we are committed to building a team that encompasses a variety of backgrounds, experiences, and skills.