Software Engineer Intern – Machine Learning Platform

Job Description

Internship, Fullstack Software Engineer, Machine Learning Platform, AI Infrastructure (Fall 2026) | Tesla

The Tone:
This is an internship at Tesla, located in Palo Alto, CA. Tesla is focused on advancing autonomy capabilities through neural networks that are trained on very large amounts of data across large-scale GPU clusters. This role is critical for building and improving the Machine Learning Platform that enables engineers and leadership to efficiently schedule, manage, and monitor machine learning experiments, data pipelines, and artifacts, ensuring robust model training at scale in the shortest amount of time.

The TL;DR
• Role: Internship
• Type: Full-time
• Location: In-person, Palo Alto, CA
• Pay: $125000 yearly
• Team: Machine Learning Platform team
• Mission: Build and improve the Machine Learning Platform that engineers and leadership use to schedule, manage, and monitor machine learning experiments, data pipelines, and artifacts, critical for scaling autonomy capabilities.
• Tech Stack: Python, React, Linux, Flask, Django, Redux, Kubernetes, relational databases, in-memory caches, message brokers

What You’ll Actually Do
• Architect: Architect and implement scalable, user-friendly tools for AI workflows to track and visualize the lifecycle of machine learning experiments and models.
• Build: Build robust tools and infrastructure, including training and evaluation code in Python to back-end and front-end work in JavaScript, to improve the machine learning team’s velocity.
• Collaborate: Collaborate closely with ML engineers to ensure tools are aligned with research needs.
• Design: Design dashboards to provide real-time insights into performance and progress for our ML engineers and leadership.
• Coordinate: Coordinate required hardware resources with the team managing the cluster hardware to maintain high availability.

The Must-Haves
• Background: Student pursuing a degree in Computer Science, Computer Engineering, or a related field of study, with a graduation date between December 2026 and December 2027.
• Experience: Working with backend infrastructure components such as relational databases, in-memory caches, and message brokers; building modern web applications using Flask/Django and React/Redux or similar component-based libraries; deploying services on Kubernetes and setting up CI/CD flows; experience working with HPC clusters.
• Skills: Strong knowledge of Python, React, and Linux; solid understanding of security principles and best practices; UI and graphic design sensibilities.
• Bonus: Knowledge of machine learning, computer vision, or neural networks.