Machine Learning Engineer Intern

WorkdayPleasanton, CA
2dOnsite

About The Position

As a Machine Learning Engineer Intern, you will play a key role in developing Workday’s intelligent core. You'll work on building the scalable machine learning platform and applications that power personalized experiences for millions of users. This is a hands-on role where you will be challenged to apply your technical skills to solve real-world problems. You'll collaborate with experienced engineers and researchers to design, train, and deploy machine learning models, including large language models (LLMs), to deliver innovative data products. In this internship, you will: Contribute to the entire ML lifecycle, from data processing to model deployment. Work with a variety of ML techniques, including deep learning, to deliver solutions that enable search and enhance user experience. Build and deploy new APIs and micro services using modern stacks like Docker and Kubernetes. Leverage Workday’s vast, exclusive datasets to deliver tangible value that helps our customers run their businesses more effectively.

Requirements

  • Currently enrolled in a bachelor’s degree program in Computer Science, Engineering, Math, Physics, or a related degree program with a graduation date no earlier than December 2026.
  • Available for a full-time in-person 12-week internship for the Summer of 2026 in Pleasanton, CA and you will return to your university program after the conclusion of the internship.
  • Relevant experience (through coursework, projects, or prior internships) with machine learning, data structures and algorithms.
  • Experience working with a programming language such as Python, Java, C++, R, JavaScript, etc.
  • Experience with one or more of the following: Natural Language Processing (NLP), AWS, SQL, Elastic search, Kubernetes, or Docker.

Nice To Haves

  • Experience with data engineering and data wrangling using libraries such as Pandas and PySpark.
  • Familiarity with large language models like Llama or GPT models and their applications.
  • Prior research or publications related to machine learning.

Responsibilities

  • Contribute to the entire ML lifecycle, from data processing to model deployment.
  • Work with a variety of ML techniques, including deep learning, to deliver solutions that enable search and enhance user experience.
  • Build and deploy new APIs and micro services using modern stacks like Docker and Kubernetes.
  • Leverage Workday’s vast, exclusive datasets to deliver tangible value that helps our customers run their businesses more effectively.
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