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.
About Out Summer Internship Program
Our Summer Internship Program is designed for students entering their final year of university who are eager to gain meaningful, real-world experience in a fast paced, collaborative, and professional environment.
As a Summer Intern, you'll participate in a comprehensive onboarding experience led by our University Relations team to set you up for success from day one. Throughout the program, you'll also have the opportunity to participate in weekly professional development sessions, networking events, social activities, and other engaging experienced designed to support your personal and professional growth.
The program takes place from June – August 2027 (10-week program).
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 hyperparameteroptimization.
- 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
Currently pursuing a Master’s degree or PhD 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
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.
The pay range posted is an hourly rate of base pay. When making an offer of employment, Veeam will take into consideration the candidate’s expectations, experience, education, scope of responsibility for the role, and the current market demands.
United States of America Intern Pay Range
$40 - $50 USD
Veeam Software is an equal opportunity employer and does not tolerate discrimination in any form on the basis of race, color, religion, gender, age, national origin, citizenship, disability, veteran status or any other classification protected by federal, state or local law. All your information will be kept confidential.
Personal data collected during the recruitment process will be processed in accordance with our Recruiting Privacy Notice, which explains how your information is collected, used, and handled in connection with hiring activities. By applying for this position, you consent to this processing.
By submitting your application, you confirm that the information provided, including any supporting documents, is complete and accurate to the best of your knowledge. Any misrepresentation, omission, or falsification may result in disqualification from consideration or, if discovered after employment begins, termination of employment.
Skills Required
- Currently pursuing a master's degree or PhD in Computer Science, Artificial Intelligence, Machine Learning, Statistics, Applied Mathematics, Data Science, Electrical Engineering, or a closely related quantitative field
- Strong interest in machine learning research, experimentation, and understanding model behavior
- Strong foundation in supervised and unsupervised learning, optimization, regularization, model evaluation, and deep learning fundamentals
- Hands-on experience training deep learning models using 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 using encapsulation, separation of concerns, modularity, and object-oriented design principles
- Comfort using Claude or similar AI tools for development, debugging, and rapid iteration
- Ability to independently investigate problems, design experiments, and critically analyze outcomes
- Advanced coursework in machine learning, deep learning, probability and statistics, linear algebra, optimization, algorithms and data structures, artificial intelligence, NLP, computer vision, reinforcement learning, or software engineering
- Experience training, fine-tuning, or evaluating transformer models or large language models
- Familiarity with Weights & Biases, MLflow, distributed training, mixed precision, LoRA, QLoRA, or hyperparameter optimization
- Experience reproducing research 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
- Availability to work in the office five days per week in San Jose, California
Veeam Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Veeam and has not been reviewed or approved by Veeam.
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Healthcare Strength — Healthcare coverage is comprehensive with options that include employee-only no-cost tiers, plus mental-health support through an assistance program. Feedback suggests these offerings compare well in tech.
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Leave & Time Off Breadth — Time off includes unlimited PTO in the U.S., paid company holidays, quarterly company-wide recharge days, and paid volunteer time. Feedback suggests team norms influence how fully this flexibility is utilized.
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Strong & Reliable Incentives — Sales and pre-sales roles feature meaningful on-target earnings with competitive base and variable structures. Feedback suggests these plans provide strong upside for high performers.
Veeam Insights
What We Do
Veeam provides a single platform for modernizing backup, accelerating hybrid cloud and securing data. Veeam has 400,000+ customers worldwide, including 82% of the Fortune 500 and 69% of the Global 2,000. Veeam’s 100% channel ecosystem includes global partners, as well as HPE, NetApp, Cisco and Lenovo as exclusive resellers, and boasts more than 35K transacting partners worldwide.
