Data and AI Internship – AI and Data Science

Job Description

Internship, Software Machine Learning Engineer, Reliability Energy Engineering (Fall 2026) | Tesla

The Tone:
This is an internship at Tesla, located on-site for a minimum of 12 weeks, starting in August or September 2026. Tesla designs and validates compelling and reliable Energy and Vehicle products. This role is critical for leveraging large-scale data and models to ensure the highest product quality and reliability, directly impacting millions of Tesla customers.

The TL;DR
• Role: Internship
• Type: Full-time (40 hours/week)
• Location: On-site
• Pay: $20.00–$50.00/hour
• Mission: Utilize data and models to enhance product design and validation, improving reliability and minimizing field failures for Tesla’s Energy and Vehicle products.
• Tech Stack: Python, SQL, Flask, FastAPI, Pyspark, Trino, Iceberg, CI/CD, version control

What You’ll Actually Do
• Build: Create robust, flexible, and automated software tools to enable complex analysis of real-time fleet data.
• Automate: Leverage AI to automate workflows and derive actionable insights from Tesla’s extensive historical data.
• Design: Develop scalable and reliable data pipelines that help Tesla understand product behavior in the field.
• Monitor: Answer complex questions on fleet usage and behavior to enable proactive monitoring, enhance reliability, and minimize field failures.
• Deploy: Design, develop, train, and deploy predictive or control models for physical degradation, usage, and system performance.

The Must-Haves
• Background: Currently pursuing a degree in Computer Science or a related field.
• Experience: Excellent software skills with proficiency in writing maintainable, production-quality code in Python; hands-on implementation experience with linear algebra, probability theory, and numerical optimization; practical experience with SQL and backend REST frameworks like Flask or FastAPI; practical experience developing and deploying AI agents, including tool-calling routines and writing/deploying skills.
• Skills: Excellent software development, Python programming, statistical modeling (linear algebra, probability theory, numerical optimization), SQL database management, AI agent development, and data pipeline design.
• Bonus: Familiarity with Big Data execution engines (e.g., Pyspark/Trino) and big data storage layers (e.g., Iceberg); familiarity with CI/CD and version control; general knowledge of physics and engineering principles.