Infrastructure Intern: Scalable Data Pipelines

Motional; Boston (MA); Hybrid; USD 28,000 - 34,000; Full time

Job summary

Motional is seeking an Infrastructure Intern to help build and optimize data pipelines, tooling, and platforms for enabling model development at scale. You will work on high‑reliability data systems, dataset processing, and infrastructure automation.

Responsibilities include scalable data ingestion, dataset management tooling, and collaboration with Perception, Behaviors, and Actions teams to refine data requirements and workflows.

Qualifications

• Pursuing a degree in Computer Science, Computer Engineering, Machine Learning, Robotics, or related field.
• Strong programming skills in Python, C++, or Go.
• Coursework or project experience in data engineering, distributed systems, automation or backend infrastructure.
• Experience with SQL and NoSQL databases.
• Familiarity with SQL and data structures.

Responsibilities

• Support scalable data ingestion, processing, and validation pipelines.
• Build tools for dataset management, versioning, and quality measurement.
• Work with large multimodal datasets (images, video, telemetry, logs).
• Automate data labeling workflows, annotation QA, and metadata tracking.
• Collaborate with Perception, Behaviors, and Actions teams to optimize dataflows.
• Contribute to observability of data pipelines (metrics, dashboards, alerts).
• Support Cloud Operations Platform for autonomous vehicle fleet management.
• Help develop Development Portal to improve SDLC workflows.

Skills

Python

C++

Golang

Data engineering

Distributed systems

Automation

Backend infrastructure

SQL

NoSQL databases

Data structures

Git

SVN

ClearCase

Education

Currently pursuing CS/CE/ML/Robotics degree

Tools

Git

SVN

ClearCase

Job description

Motional is seeking an Infrastructure Intern to help build and optimize data pipelines, tooling, and platforms for enabling model development at scale. You will work on high‑reliability data systems, dataset processing, and infrastructure automation.

Responsibilities include scalable data ingestion, dataset management tooling, and collaboration with Perception, Behaviors, and Actions teams to refine data requirements and workflows.