Machine Learning Engineer Intern – ML Systems Engineering

Job Description

Internship, Software Engineer, AI Inference (Summer 2026) | Tesla

The Tone:
This is an on-site internship at Tesla, located in Palo Alto, CA, targeting students for Summer 2026. Tesla is an organization that puts machine learning models into production, training and deploying large neural networks for efficient inference on compute-constrained edge devices such as CPUs, GPUs, and in-house AI ASICs. This multi-disciplinary role sits at the intersection of machine learning and systems, focusing on building the crucial ML frameworks and infrastructure that enable the seamless training, deployment, and inference of all neural networks that run at Tesla AI. The position is essential for experimenting with novel architectures under constrained compute and developing the robust infrastructure to deploy them effectively.

The TL;DR
• Role: Internship
• Type: Full-time
• Location: In-person, Palo Alto, CA
• Pay: $100000–$150000 yearly
• Team: The team puts ML models into production, training and deploying large neural networks for efficient inference on compute-constrained edge devices.
• Mission: To experiment with novel architectures under constrained compute and build the infrastructure to deploy such architectures.
• Tech Stack: Python, C/C++, PyTorch, CUDA

What You’ll Actually Do
• Framework Development: Build robust AI frameworks to lower neural networks to edge devices.
• Infrastructure Creation: Build robust AI infrastructure to train and fine-tune networks for Tesla AI.
• Network Deployment: Deploy state-of-the-art neural networks on Tesla’s in-house AI ASIC, with an aim to maximize network performance while minimizing latency.
• Model Optimization: Collaborate with AI scientists and compiler engineers to effectively compress large models to run in low precision.

The Must-Haves
• Background: Student actively pursuing a degree in Computer Science, Computer Engineering, or a relevant field of study, with an anticipated graduation date between December 2026 and August 2027. A minimum of 12 weeks, full-time (40 hours/week) and on-site commitment is required for this internship.
• Experience: Proficiency with training and deploying neural networks for real-world AI.
• Skills: Proficiency with PyTorch or another machine learning framework. Proficiency with computer systems and computer architecture. Experience with CUDA.
• Bonus: Proficiency with Python, C/C++.