About the Team
The Deployment Technology team in our Product & Engineering organization is actively looking for a seasoned, highly technical and mission-driven Principal, Machine Learning. This is an exciting cross-functional role where you will work in partnership with a variety of stakeholders including but not limited to Product, Engineering, Technology, Design, Community, Services, Solution Marketing, and Solution Management. You will uncover insights, identify opportunities for product improvements and new product development, define product metrics with goals, and design experiments that drive adoption and engagement of Workday's products and help grow the business.

About the Role

• Lead the ML strategy for global deployment initiatives, driving faster, safer, and more predictable customer onboarding
• Architect and deliver advanced analytical, statistical, and machine learning solutions that optimize data migration, configuration validation, risk detection, and adoption outcomes across customer environments
• Partner with global stakeholders - including product, engineering, customer success, and implementation teams - to embed data-driven decisioning directly into deployment tooling and workflows
• Define success metrics and experimentation frameworks, establishing the leading indicators for customer adoption, time-to-value, and deployment quality across regions and industries
• Influence product roadmaps by translating complex insights into actionable strategic recommendations for senior leadership and stakeholders

About You

Basic Qualifications

12+ years experience in machine learning development, leading ML research and development initiatives, designing complex ML systems, and ensuring the scalability and performance of ML models in production.
[Insert years] experience in advanced machine learning methodologies, distributed ML frameworks, and cloud-based ML platforms including [insert methodologies, frameworks, and platforms].
Bachelor's degree in a relevant discipline such as Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related discipline, or equivalent practical experience; a Master's or PhD in a relevant discipline is strongly preferred.

Other Qualfications

Expert-level ability in Data Processing, including [insert specific cutting-edge techniques or tools], to architect and optimize data pipelines for large-scale machine learning.
Deep and strategic knowledge of Data Science principles and their application in [insert specific expert-level areas like research or novel algorithm development].
Proven ability to lead Exploratory Data Analysis (EDA) initiatives to [insert specific strategic actions like defining data strategy or uncovering fundamental insights].
Mastery of Feature Engineering methods to [insert specific actions like developing innovative feature representations or addressing complex data challenges].
Expert-level knowledge of a broad range of Machine Learning algorithms and their strategic application in [insert specific complex and novel problem domains].
Proven ability to lead Model Building processes and [insert specific advanced and novel modeling techniques].
Mastery of the Model Development lifecycle and experience in [insert specific expert-level stages like designing robust deployment architectures or addressing model drift at scale].
Deep expertise in Model-Based Design (MBD) concepts and their application in [insert relevant complex and strategic application areas].
Mastery in Python (Programming Language) and a comprehensive understanding of the ecosystem for data science and machine learning, including [insert specific advanced and specialized libraries].
Strong understanding of Software Development principles and extensive experience in architecting and deploying scalable and reliable machine learning systems in production.
Exceptional Team Collaboration and leadership skills, with the ability to guide and mentor senior team members and influence organizational best practices.

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 click here.

Primary Location: USA.CA.Pleasanton

Primary Location Base Pay Range: $228,000 USD - $342,000 USD

Additional US Location(s) Base Pay Range: $190,600 USD - $342,000 USD

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.