Applied Machine Learning Engineering Intern

About Gusto

At Gusto were on a mission to grow the small business economy. We handle the hard stufflike payroll health insurance 401(k)s and HRso owners can focus on their craft and customers. With teams in Denver San Francisco and New York were proud to support more than 400000 small businesses across the country and were 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 teams roadmap directly advancing Gustos mission.

At Gusto we are committed to leveraging data to build the products of the future. As an Applied Machine Learning Engineering Intern youll be at the forefront of this effort focusing on the end-to-end development of production-level machine learning systems. Youll 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: Well 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 youll 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.

Heres what youll do day-to-day (and well support you so youre 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.

Heres what were looking for:

• Currently pursuing a Masters ( 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 Gustos 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 its 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 toGustos Applicant Privacy Notice.