About the Team
Agent Factory is where Workday’s next chapter gets built. We’re forming small, senior, cross-functional AI teams that bring together product leaders, machine learning engineers, and full-stack builders to create intelligent agents used by millions of people every day. This is production-grade AI—deeply embedded into Workday’s platform—not research experiments or maintenance work. Teams own problems end to end, collaborate tightly across disciplines, and use the right tools to solve real customer challenges at global scale. You’ll work at the intersection of AI, platform architecture, and human workflows, with the autonomy to shape how agents reason, act, and scale responsibly. High trust, high expectations, and real impact. Engineering, but brighter.
About the Role
As a ML Engineer, you will help develop data & AI-driven, automated, comprehensive solutions at global scale for all size and types of enterprise using modern software, data, and AI engineering stacks.
- Work closely with product managers, software engineers to deliver AI solutions that provide payroll administrators and users enormous value and efficiency. Your work will also ensure that users have the best payroll processing experience by providing predictive analytics and recommendations.
- You will use Workday’s AI development environment and resources on rich HR and Payroll datasets to deliver value that transforms the way our customers use Payroll products.
- Opportunity to apply your highly technical problem solving, creative thinking, alluring mind using the latest AI Agent technologies and toolsets and make a huge impact on the world's largest enterprises that use Workday to process payroll for millions of employees.
About You
Basic Qualifications:
- 5+ yrs experience as part of a data science, machine learning software development team or relevant work in a PhD or equivalent experience program.
- 3+ years experience using Python and frameworks such as Pytorch, TensorFlow
- 2+ years of experience related to machine learning, deep learning, NLP, GenAI, multi-agent AI systems, distributed training, model hosting, etc
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Other Qualifications:
- B.S. or M.S. in relevant fields (Computer Science, Mathematics, Engineering). PhD or equivalent experience preferred
- Experienced in handling large-scale, complex data sets, data modeling, and productizing machine learning algorithms.
- Be part of a team of data scientists and software developers and learn all about HR and Payroll data and processes
- Own data exploration and transformation, feature & prompt engineering, design and enhance ML models/frameworks
- Strong experience building applied machine learning products, including taking a product through design, implementation, and to production is a plus.
Workday Pay Transparency Statement
The annualized base salary ranges for the primary location and any additional locations are listed below. Workday 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 .
Primary Location: USA.CO.BoulderPrimary Location Base Pay Range: $143,400 USD - $215,200 USD
Additional US Location(s) Base Pay Range: $136,200 USD - $240,000 USD
Additional Considerations:
The application deadline for this role is the same as the posting end date stated as below:
06/20/2026
Our Approach to Flexible Work
With 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.
