Applied Machine Learning Engineering Intern
at Gusto, Inc.
San Francisco, United States
About Gusto
At Gusto, we're on a mission to grow the small business economy. We handle the hard stuff—like payroll, health insurance, 401(k)s, and HR—so owners can focus on their craft and customers. With teams in Denver, San Francisco, and New York, we’re proud to support more than 400,000 small businesses across the country, and we’re building a workplace that represents and celebrates the customers we serve. Learn more about our Total Rewards philosophy.
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.
Gusto has physical office spaces in Denver, San Francisco, and New York City. Employees who are based in those locations will be expected to work from the office on designated days approximately 2-3 days per week (or more depending on role). The same office expectations apply to all Symmetry roles, Gusto's subsidiary, whose physical office is in Scottsdale.
Note: The San Francisco office expectations encompass both the San Francisco and San Jose metro areas.
When approved to work from a location other than a Gusto office, a secure, reliable, and consistent internet connection is required. This includes non-office days for hybrid employees.
Our customers come from all walks of life and so do we. We hire great people from a wide variety of backgrounds, not just because it's the right thing to do, but because it makes our company stronger. If you share our values and our enthusiasm for small businesses, you will find a home at Gusto.
Gusto is proud to be an equal opportunity employer. We do not discriminate in hiring or any employment decision based on race, color, religion, national origin, age, sex (including pregnancy, childbirth, or related medical conditions), marital status, ancestry, physical or mental disability, genetic information, veteran status, gender identity or expression, sexual orientation, or other applicable legally protected characteristic. Gusto considers qualified applicants with criminal histories, consistent with applicable federal, state and local law. Gusto is also committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. We want to see our candidates perform to the best of their ability. If you require a medical or religious accommodation at any time throughout your candidate journey, please fill out this form and a member of our team will get in touch with you.
Gusto takes security and protection of your personal information very seriously. Please review our Fraudulent Activity Disclaimer.
Personal information collected and processed as part of your Gusto application will be subject to Gusto's Applicant Privacy Notice.
