Senior Principal Machine Learning Engineer

Your work days are brighter here.

At Workday, it all began with a conversation over breakfast. When our founders met at a sunny California diner, they came up with an idea to revolutionize the enterprise software market. And when we began to rise, one thing that really set us apart was our culture. A culture which was driven by our value of putting our people first. And ever since, the happiness, development, and contribution of every Workmate is central to who we are. Our Workmates believe a healthy employee-centric, collaborative culture is the essential mix of ingredients for success in business. That’s why we look after our people, communities and the planet while still being profitable. Feel encouraged to shine, however that manifests: you don’t need to hide who you are. You can feel the energy and the passion, it's what makes us unique. Inspired to make a brighter work day for all and transform with us to the next stage of our growth journey? Bring your brightest version of you and have a brighter work day here.

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About the Team

Are you motivated by witnessing machine learning/AI products come to life in production settings which impact tens of millions of people? As part of a global, high-growth technology company, our work supports thousands of the largest global companies and more than 30 million end users. Workday’s Machine Learning organization is bringing “AI first” products to life at every step of the Workday product offering. We’re looking for highly creative, results-focused, and deeply skilled machine learning engineers/scientists to join us in building innovative AI solutions.

About the Role

As a Senior Principal ML Engineer, you will be a key technical leader and visionary, driving the development and application of machine learning across Workday's product ecosystem. This includes:

• Architecting advanced AI systems and agents: You will drive the design and implementation of sophisticated AI systems, with a strong focus on agentic AI capabilities encompassing planning, reasoning, and action execution frameworks, while also addressing a broader range of complex machine learning challenges, ensuring solutions are both scalable and performant.

• Mentoring and guiding engineers: You will provide technical leadership and mentorship to a team of dedicated ML engineers, fostering a culture of innovation and collaboration.

• Collaborating with product and engineering: You'll partner with product managers and engineering teams to define product roadmaps and ensure successful integration of AI solutions across Workday's HR, Finance, and Planning products.

• Staying ahead of the curve: You will keep abreast of the latest advancements in machine learning and AI research, identifying and evaluating new technologies for potential adoption.

We will challenge you to apply your deep expertise, critical thinking, and leadership skills to make a significant impact on thousands of enterprises and millions of users. If you are a passionate and experienced ML leader eager to shape the future of AI at Workday, we'd love to hear from you.

About You

Basic Qualifications

• Bachelor's degree in a relevant field, such as Computer Science, Mathematics, or Engineering.

• 12+ years experience working on a data science, machine learning or related software development team.

• 12+ years experience in Python and supporting numeric libraries, with experience in shipping production code and models.

• 10+ years experience in machine learning and deep learning frameworks & toolkits such as Pytorch and Sklearn

Other Qualifications

• PhD or MS degree in a relevant field, such as Computer Science, Mathematics, or Engineering. Publications in machine learning research are helpful.

• Practical experience with generative models, large language models (LLM), retrieval augmented generation (RAG) systems, transformer neural networks.

• Experience with cloud computing platforms (e.g. AWS, GCP), containerization technologies (e.g. Docker) and data engineering pipelines (e.g. ETL)

• Experience developing and deploying machine l