Machine Learning Engineer Intern

Workday•Pleasanton, CA

31d•$154,500•Onsite

About The Position

The Workday Machine Learning team researches, builds, and deploys the engine that powers the heart of Workday’s intelligent core — a platform supporting 37+ million users and growing. Our engineers work with innovative technologies and help build real-life products that improve the lives of the world’s professionals. Our mission is to make machine learning and AI core to Workday’s products. We build data products and AI solutions designed to scale across hundreds of use cases throughout the Workday platform. Our team is passionate about teaching and learning, so bring your curiosity, share your perspective, and learn with us as we change the way millions of people work. As a Machine Learning Engineer Intern, you’ll help develop Workday’s intelligent core by contributing to the scalable AI and ML platforms that power personalized experiences for millions of users. Working alongside experienced engineers and researchers, you’ll help design, implement, and deploy machine learning models and large language model applications that support innovative data products. Most of your time will be spent writing production-quality code, running experiments, and working with large datasets to improve model and system performance. This is an opportunity to apply your software engineering and machine learning knowledge to real-world products that support customers at scale.

Requirements

Currently enrolled in a Bachelor’s or Master's degree program in Computer Science, Machine Learning, Data Science, Artificial Intelligence, Software Engineering, Computer Engineering, Mathematics, Statistics, or a related degree program
Less than 12 months of previous professional work experience
Anticipated graduation date between December 2027 and June 2028
Available for a full-time, in-person, 12-week internship for the Summer of 2027 in the listed locations, and you will return to your university degree program after the conclusion of the internship
Experience with both software engineering and machine learning engineering concepts through coursework, research, internships, or personal projects
Experience programming in Python or another language used for machine learning, data processing, or software development
Experience with one or more of the following: Retrieval-Augmented Generation (RAG), Natural Language Processing (NLP), Pandas, PySpark, or AWS
Familiarity with AI tooling such as Gemini, Claude, Cursor, Codex, or similar tools

Nice To Haves

Interest in LLM-based approaches, such as retrieval, prompt tuning, embeddings, or model evaluation
Curiosity and eagerness to learn, with an interest in how AI and ML systems are developed, tested, deployed, and improved over time
Excellent communication skills, both verbal and written, with the ability to share technical ideas clearly and collaborate across teams

Responsibilities

Contribute across the full machine learning lifecycle, from data processing and experimentation through model and system deployment
Apply machine learning and AI techniques, including deep learning and LLM-based approaches such as retrieval and prompt tuning, to power search and enhance the user experience
Write production-quality code and build scalable components that support AI and ML products across the Workday platform
Build and deploy APIs and microservices using a modern engineering stack, including Docker and Kubernetes
Design and run evaluations to measure model and system quality, using results to guide what to improve or build next