About the Role:
Our Applied Machine Learning Engineering internship is a 12-week hybrid summer experience focused on making a significant impact on our customers by being embedded directly into our data teams. Each intern is paired with a dedicated mentor and a team manager, providing guidance and support as they make immediate contributions to the team’s roadmap, directly advancing Gusto’s mission.
At Gusto, we are committed to leveraging data to build the products of the future. As an Applied Machine Learning Engineering Intern, you'll be at the forefront of this effort, focusing on the end-to-end development of production-level machine learning systems. You'll gain hands-on experience in building, deploying, and maintaining models that directly impact our customers and our business. Your work will directly support teams across the company, helping to build new features, optimize our operations, and improve products for hundreds of thousands of small businesses.
Please note: We’ll be offering only one cohort start and end date (May 18 - August 7, 2026).
Deadline to Apply: Tuesday, November 25, 2025
About the Team:
Our Applied Machine Learning Engineers solve some of the hardest problems our small business customers present to us. How can we introduce features in a way that is inspirational and engaging? And how to make those recommendations timely based on the problems or opportunities in front of them? By joining our team, you’ll not only learn the fundamentals of AI and Machine Learning delivery but also how to greatly enhance your impact by curating an entire customer journey.
Here’s what you’ll do day-to-day (and we’ll support you so you’re great at it):
- Build and deploy scalable machine learning models and pipelines in a production environment.
- Write production-quality code to integrate models into our core platform and products.
- Work with diverse teams across product, engineering, and data to understand business problems and translate them into machine learning solutions.
- Develop and maintain monitoring systems to ensure the performance and reliability of deployed models.
- Partner with Data Scientists to evaluate and test models to prepare them for production.
Here’s what we're looking for:
- Currently pursuing a Master's ( with an expected graduation date between December 2026 and June 2027) or PhD (graduating between December 2026 and June 2028) in Computer Science or a related technical field.
- Strong programming skills in Python and experience with machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch).
- Experience leveraging AI effectively as a development partner to offload manual tasks, explore new approaches, or evaluate the end-to-end performance.
- Experience with cloud platforms (e.g., AWS, GCP) and familiarity with big data technologies (e.g., Spark, Hive).
- Understanding of the full ML lifecycle, including data preprocessing, feature engineering, model training, evaluation, deployment, and monitoring.
- Familiarity with LLM applications is desired but not required. We continue to explore how our work can feed into agentic solutions for our customers.
- Excellent communication and collaboration skills with the ability to work in a cross-functional environment.
- A passion for building robust, scalable systems and solving real-world problems.
- U.S. work authorization is required. This role is not available for sponsorship.
- This is a hybrid role and will require you to be in the office at least twice a week in our San Francisco. Relocation assistance will be provided during your internship.
Pay and benefits
Our cash compensation range for this role for graduate students is $78.37/hr to $85.58/hr in San Francisco.
