AI/ML Intern Summer 2027

About the Role

Internship Dates: June – August 2027 (10-week program)

Location: San Jose, California (5 days a week in office)

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.

Key Responsibilities

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

Requirements & Tech Stack

• 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.

Qualifications

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

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.

Internship Benefits

• Paid Company Holidays
• Tech Stipend
• 8 Hours of Paid Volunteer Time
• Personal and Professional Development through the Internship Program

Intern Pay Range

$40 - $50 USD per hour