AI Intern- Summer 2026

Summer Internship

Our Summer Internship is designed for students leading into their final year of university, who want to gain real life work experience in a fast past, exciting and professional environment.

As a Summer Intern, you will participate in onboarding with the UR team that will set you up for success in your role. You will also benefit from professional development sessions, networking, and social events provided by the Internship Program.

The program takes place from June – August 2026 (12 week program)

Language Model Development, Machine: Learned Threat Detection, Agent-Based: Interactive Training Simulators

What We're Looking For

• Passion & Curiosity: Strong interest in machine learning research, experimentation, and understanding model behavior.
• Machine Learning Fundamentals: Strong foundation in supervised/unsupervised learning, optimization, regularization, model evaluation, and deep learning fundamentals.
• Model Training Experience: Hands-on experience training deep learning models in PyTorch or TensorFlow. Ability to diagnose poor convergence, overfitting, unstable training, gradient issues, data leakage, and weak generalization.
• Statistics & Experimentation: Strong understanding of probability, statistics, hypothesis testing, experimental analysis, and interpreting noisy results.
• Software Engineering Discipline: Ability to write clean, maintainable code with strong encapsulation, separation of concerns, modularity, and object-oriented design principles.
• Rapid Prototyping: Comfortable using Claude or similar AI tools for development, debugging, and rapid iteration.
• Research Mindset: Ability to independently investigate problems, design experiments, and analyze outcomes critically.

Nice To Have

• LLM Experience: Experience training, fine-tuning, or evaluating transformer models or LLMs.
• Modern ML Tooling: Familiarity with Weights & Biases, MLflow, distributed training, mixed precision, LoRA/QLoRA, or hyperparameter optimization.
• Research Exposure: Experience reproducing papers, participating in ML competitions, contributing to research projects, or building advanced personal projects.
• Applied AI Domains: Exposure to NLP, generative AI, multimodal systems, retrieval systems, or recommendation systems.

What You Could Be Working On

• Model Training & Evaluation: Train and improve ML models across a variety of datasets and tasks.
• Training Diagnostics: Analyze loss curves, gradients, metrics, and experiments to diagnose model failures and improve performance.
• LLM & Generative AI Research: Work on transformer models, fine-tuning workflows, evaluation systems, and generative AI applications.
• Rapid Experimentation: Prototype and iterate quickly using Claude-assisted development workflows.
• Research Tooling: Build reusable experimentation, training, and evaluation workflows for ML research.

Candidates should have completed advanced coursework in areas such as:

Machine Learning
Deep Learning
Probability & Statistics
Linear Algebra
Optimization
Algorithms & Data Structures
Artificial Intelligence
Natural Language Processing
Computer Vision
Reinforcement Learning
Software Engineering
Targeted Field of Study

Targeted Field of Study Currently pursuing a Bachelors or Master’s degree in:

Computer Science
Artificial Intelligence
Machine Learning
Statistics
Applied Mathematics
Data Science
Electrical Engineering
Or other closely related quantitative fields

Requirements:

• This role requires you to be in office 5 days a week at the San Jose, California location

Applicants must be authorized to work in the U.S. We are unable to sponsor or take over sponsorship of an employment Visa now or in the future.

Benefits

As a paid intern at Veeam, you’ll receive:

• Paid Company Holidays during your internship
• Tech Stipend to help set up your workspace
• 8 Hours of Paid Volunteer Time through our Veeam Cares Program
• Personal and Professional Development through our Internship Program

We’re committed to providing a supportive and rewarding internship experience.