About the TeamThe 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.
About the RoleAs 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.
Key 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
Workday Early Career Programs:In addition to collaborating with experienced Machine Learning Engineers, you'll engage in our Early Career Programs - specifically structured to support and empower you to succeed throughout your internship!
Workday Intern ProgramBrighter work days start with real work and real support from a community that helps you shine from day one. During our in-person internship experience, you'll jump into meaningful projects and see how your ideas can help shape the future of work.
Interns build enterprise skills through applied learning, personalized coaching, and connection events designed so our Early Talent can bring their best self to work. If you're invested in your growth, team-oriented, and ready to bring fresh ideas to work that makes an impact, we'd love to meet you. The future is now - apply today to launch your career as a member of the Workday Intern Program.
P&T Atmosphere:As a member of the Product & Technology org, you'll participate in our P&T Atmosphere program - a dedicated investment in your growth that offers tailored technical training and deep dives into the Workday ecosystem. This specialized program equips you with job-critical skills and connects you directly with P&T leaders and peers to fast-track your technical career.
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About YouBasic Qualifications:- 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 6-month internship starting in February 2027 and ending August 2027 in the Vancouver office, and you will return to your university degree program after the conclusion of the internship
- Available for a full-time, in-person 12-week internship starting in May 2027 and ending August 2027 in the Toronto office, 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
Other Qualifications:
- 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
Visa sponsorship is not available for this role.Workday Pay Transparency StatementWorkday pay ranges vary based on work location. As a part of the total compensation package, this role may be eligible for the Workday Bonus Plan or a role-specific commission/bonus, as well as annual refresh stock grants. Recruiters can share more detail during the hiring process. Each candidate's compensation offer will be based on multiple factors including, but not limited to, geography, experience, skills, job duties, and business need, among other things. For more information regarding Workday's comprehensive benefits, please click here.
Primary Location: CAN.BC.Vancouver
Primary CAN Base Pay Range: $66,400 - $99,600 CAD
Our Approach to Flexible WorkWith Flex Work, we're combining the best of both worlds: in-person time and remote. Our approach enables our teams to deepen connections, maintain a strong community, and do their best work. We know that flexibility can take shape in many ways, so rather than a number of required days in-office each week, we simply
spend at least half (50%) of our time each quarter in the office or in the field with our customers, prospects, and partners (depending on role). This means you'll have the freedom to create a flexible schedule that caters to your business, team, and personal needs, while being intentional to make the most of time spent together. Those in our remote "home office" roles also have the opportunity to come together in our offices for important moments that matter.
