Summer 2027: AI Science Intern

To qualify for US internships, you must be currently enrolled in a degree-seeking program with an expected graduation date after the internship/co-op ends. If you do not meet this requirement, we invite you to explore other opportunities available on our careers website.

Intuit internships are 12 weeks throughout the summer. We have fixed start and end dates that are designed to work with various universities’ academic calendars.

• Cohort 1: Monday, May 17 - Friday, August 6, 2027 (12 weeks)
• Cohort 2: Monday, June 14 - Friday September 3, 2027 (12 weeks)

About our Emerging Talent Program:

Intuit invests in Emerging Talent because fresh perspectives strengthen our products and teams. The program is backed by a culture that values curiosity and collaboration, and you'll be supported by dedicated managers and mentors who are invested in your growth. As an intern or co-op, you'll work on meaningful projects with business impact, many centered on AI and emerging technologies, and contribute to driving decisions. You'll build skills through function-specific learning opportunities, connect with a global community of interns and co-ops through dedicated programming and social events, and get exposure to senior leadership and cross-functional work across Intuit's product ecosystem. Learn more about our Intern and Co-op Program here.

As an AI Scientist Intern at Intuit, you won't just be observing; you'll be on the front lines. You'll work side-by-side with our world-class AI Scientists, Researchers and Machine Learning Engineers, collaborating with Data Analysts, Software Engineers, and Product Managers. This is your chance to uncover critical insights and develop powerful machine learning models that directly understand and enhance customer experiences across Intuit's products.

Previous AI Scientist Interns have worked on projects such as improving customer experiences by applying adversarial deep learning to ranking algorithms and assessing call quality using transcript data; innovating with NLP and deep learning to link form lines to documentation, build temporal recommendation models, and develop unsupervised knowledge acquisition for Q&A systems; forecasting and prediction through transaction time series forecasting, real-time churn prediction, and predicting cognitive biases with financial data; and enhancing model training by exploring active learning for event labels and creating customer intent classifiers for digital assistants.

Responsibilities

• Gather, clean, and explore large, real-world datasets to uncover patterns and prepare them for modeling, including your own data wrangling and ETL.

• Build, train, and evaluate machine learning and deep learning models using techniques such as classification, regression, clustering, and neural networks.

• Engineer and refine features from raw data, developing intuition for what drives model performance.

• Design and run experiments (e.g., A/B tests), perform statistical analysis, and communicate the impact of your models to peers and leaders.

• Dive into current AI/ML research and methodologies, including generative AI and LLMs, to inform new solutions and stay ahead of the curve.

• Partner with AI Scientists, Machine Learning Engineers, Data Analysts, Software Engineers, and Product Managers to translate insights into product impact.

• Develop proofs-of-concept for innovative, AI-driven features or solutions.

• Create clear documentation of your research, model architectures, code, and experimental results for both technical and non-technical audiences.

Qualifications

• Currently enrolled in a PhD program in Computer Science or a related technical field. Alternatively, a Bachelor's or Master's program with prior relevant experience and a graduation date after the internship ends.

• Must be legally authorized to work in the United States on a full-time basis for the duration of the internship.

• Ability to work in a hybrid environment at an Intuit office location determined by your team and role (relocation stipend provided).

• Familiarity with core machine learning techniques (regression, classification, clustering, optimization) and their mathematical foundations.

• Ability to explore, discover, and import data from multiple sources and make it machine-learning ready.

• Strong programming skills in Python; SQL proficiency.

• Curiosity about generative AI and large language models, and interest in applying AI tools to accelerate your own work.

• Excellent communication skills and a learning mindset.

Intuit provides a competitive compensation package with a strong pay for performance rewards approach. This position may be eligible for a cash bonus, equity rewards and benefits, in accordance with our applicable plans and programs (see more about our compensation and benefits at Intuit®: Careers | Benefits). Pay offered is based on factors such as job-related knowledge, skills, experience, and work location. To drive ongoing fair pay for employees, Intuit conducts regular comparisons across categories of ethnicity and gender. The expected base pay range for this position is: $42.69 - $86.68 /hr. The expected base pay range for this position is: Mountain View $50.5 - $89.5 New York $49.5- $86.5 San Diego, CA $45- $82