Data & ML Platform Intern - Build Scalable Pipelines

Auror Limited; Mountain View (CA); On-site; USD 65,000 - 80,000; Full time

Job summary

Aurora is seeking a Summer 2027 Data & ML Platform Engineering Intern to help build scalable data pipelines and ML platform tooling. You will work with data engineers and ML teams to convert raw sensor data into model-ready datasets using AWS/GCP infrastructure.

The role requires pursuing CS/Data Eng degrees, strong Python or Golang skills, and hands-on experience with backend data systems. In-person office presence is expected in Mountain View or San Francisco.

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.

Responsibilities

• 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.

Skills

Python

Golang

ETL concepts

CAP theorem

AWS

GCP

ML exposure

Backend systems

Education

Bachelor's or Master's in CS/Data Eng

Tools

AWS

GCP

Job description

Aurora is seeking a Summer 2027 Data & ML Platform Engineering Intern to help build scalable data pipelines and ML platform tooling. You will work with data engineers and ML teams to convert raw sensor data into model-ready datasets using AWS/GCP infrastructure.

The role requires pursuing CS/Data Eng degrees, strong Python or Golang skills, and hands-on experience with backend data systems. In-person office presence is expected in Mountain View or San Francisco.