Job description

Who we are Aurora’s mission is to deliver the benefits of self-driving technology safely, quickly, and broadly. The Aurora Driver aurora.tech will create a new era in mobility and logistics, one that will bring a safer, more efficient, and more accessible future to everyone. At Aurora, you will tackle massively complex problems alongside other passionate, intelligent individuals, growing as an expert while expanding your knowledge. For the latest news from Aurora, visit aurora.tech aurora.tech or follow us on LinkedIn linkedin.com. What we are looking for We're searching for Summer 2027 Data & ML Platform Engineering Intern. You'll join one of the teams building the infrastructure that makes Aurora's ML work at scale — data pipelines, ML platforms, labeling and data-engine systems, distributed compute, and the cloud tooling that turns raw sensor and behavioral data into model-ready datasets. In this role you will - Build and maintain data pipelines and workflow automation that turn raw fleet and sensor data into model-ready datasets - Design or extend ML platform tooling (labeling systems, data engines, distributed compute) used across autonomy teams - Use cloud infrastructure (AWS/GCP) to scale data ingestion, storage, and processing workloads - Partner with ML engineers to understand downstream model requirements and translate them into pipeline/platform design decisions - Instrument systems for observability and help harden a prototype into something that can run in production Required qualifications - Currently pursuing a Bachelor's or Master's degree in Computer Science, Data Engineering, or a related field - Strong programming skills in Python and/or Golang - Working knowledge of data pipeline/ETL concepts and basic distributed systems tradeoffs (e.g. CAP theorem) - Experience with cloud platforms (AWS or GCP) - Some applied exposure to ML, robotics, maps/geospatial systems, or a comparable domain - Hands-on experience building or extending a backend system or pipeline with real scale-up/scale-out requirements Desired qualifications - Experience with parallel execution / distributed processing frameworks (e.g. Spark, Ray, Dask) - Fluency with AI/agentic coding tooling - Prior internship or industry experience with production data infrastructure Compensation The hourly pay rate for this internship in Mountain View or San Francisco is: - $52.00 per hour for interns pursuing a bachelor’s degree; and - $58.00 per hour for interns pursuing a master’s degree The hourly pay rate for this internship in Pittsburgh is: - $47.00 per hour for interns pursuing a bachelor’s degree; and - $52.00 per hour for interns pursuing a master’s degree Working at Aurora At Aurora, we bring together extraordinarily talented and experienced people united by the strength of our values. We operate with integrity, set outrageous goals, and build a culture where we win together — all without any jerks. We believe in-person work increases collaboration, empathy, and our ability to lead effectively. As a result, Aurorans are expected to work from the office at least 3 days per week, with some roles requiring more frequent in-office presence, up to 5 days per week, based on operational needs. Our Careers page aurora.tech provides insight into what it is like to work at Aurora, and you can find all the latest updates in our Newsroom aurora.tech. Our commitment to safety At the core of everything we do is our commitment to safety. Building best-in-class self-driving technology will take time, and we believe that each employee at Aurora has a role in contributing to safety, every step of the way. Aurora expects commitment to our safety policies from every employee, and seeks candidates who take an active responsibility, can contribute to building an atmosphere of trust, and invest in the organization’s long-term success by prioritizing working safely, no matter what. Our commitment to inclusion Aurora considers candidates without regard to their race, color, religion, national origin, age, sex, gender, gender identity, gender expression, sexual orientation, marital status, pregnancy status, parent or caregiver status, ancestry, political affiliation, veteran and/or military status, physical or mental disability, or any other status protected by federal or state law. Aurora considers qualified applicants with criminal histories, consistent with applicable federal, state, and local law. We are also committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If you need assistance or an accommodation due to a disability, you may contact us at careersiteaccommodations@aurora.tech. For California applicants, information collected and processed as part of your application and any job applications you choose to submit is subject to Aurora’s California Employment Privacy Policy.

Requirements

Must-haves

Currently pursuing a Bachelor's or Master's degree in Computer Science, Data Engineering, or a related field
Strong programming skills in Python and/or Golang
Working knowledge of data pipeline/ETL concepts and basic distributed systems tradeoffs (e.g. CAP theorem)
Experience with cloud platforms (AWS or GCP)
Some applied exposure to ML, robotics, maps/geospatial systems, or a comparable domain
Hands-on experience building or extending a backend system or pipeline with real scale-up/scale-out requirements

Nice-to-haves

Experience with parallel execution / distributed processing frameworks (e.g. Spark, Ray, Dask)
Fluency with AI/agentic coding tooling
Prior internship or industry experience with production data infrastructure

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

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Platform: ashby
Effort: quick