AI Intern- Summer 2026

Veeam Software•San Jose, CA

7h•Onsite

About The Position

Veeam is the Data and AI Trust Company, specializing in helping organizations ensure their data and AI are fully understood, secured, and resilient to enable the acceleration of safe AI at scale. As the market leader in both data resilience and data security posture management, Veeam is built for the convergence of identity, data, security, and AI risk. Headquartered in Seattle with offices in more than 30 countries, Veeam protects over 550,000 customers worldwide, who trust Veeam to keep their businesses running. Join us as we go fearlessly forward together, growing, learning, and making a real impact for some of the world’s biggest brands. 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)

Requirements

Strong interest in machine learning research, experimentation, and understanding model behavior.
Strong foundation in supervised/unsupervised learning, optimization, regularization, model evaluation, and deep learning fundamentals.
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.
Strong understanding of probability, statistics, hypothesis testing, experimental analysis, and interpreting noisy results.
Ability to write clean, maintainable code with strong encapsulation, separation of concerns, modularity, and object-oriented design principles.
Comfortable using Claude or similar AI tools for development, debugging, and rapid iteration.
Ability to independently investigate problems, design experiments, and analyze outcomes critically.
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.
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.
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.

Nice To Haves

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

Responsibilities

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.