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
Do you want to build impactful, machine learning features and solutions that will be used by millions of end-users? The Machine Learning organization at Workday solves challenging problems that lie at the intersection of machine learning and enterprise-scale software. The team builds sophisticated ML solutions that power the core Workday software by modeling user behavior and providing intelligent automation. Come join us and make easier and balanced for millions of Workday users!About the Role
As a Principal Software Development Engineer for Machine Learning, you will be a pivotal technical contributor, working closely with machine learning engineers to architect, build, and deploy robust, scalable, and performant AI systems across Workday's product ecosystem. You will play a key role in transforming innovative ML research into production-ready solutions, primarily agentic AI capabilities encompassing planning, reasoning, and action execution frameworks.
Your primary focus will be to:
Drive Architectural Design and Implementation: Own the architectural design and implementation of sophisticated AI systems and agentic AI capabilities, with a focus on advanced patterns such as tool calling, supervisor agents, multi-agent architectures, and human-in-the-loop integration. Ensure solutions are highly scalable, performant, and resilient in production environments, defining technical roadmaps and standard methodologies for ML system development and MLOps.
Build and Deploy Core ML Infrastructure: Architect, implement, and deploy secure, RESTful web services in Python and Kubernetes. Design and build robust, multi-tenant runtime architectures enabling fast inference and scaling to millions of users, seamlessly integrating with existing Workday components and leveraging cloud deployment standard methodologies.
Develop and Optimize Data Pipelines: Lead the development and deployment of Python and Spark-based data pipelines for collecting, joining, transforming, and loading large-scale datasets essential for model training and inference. Focus on efficiency, reliability, and data quality.
Technical Leadership and Mentorship: Provide technical leadership and guidance to fellow engineers, fostering a culture of engineering excellence, advocating for software development standard methodologies, and participating in design reviews and code quality initiatives.
You will also:
Collaborate multi-functionally to translate requirements into technical designs, taking ownership of creative, high-quality solutions.
Apply and continuously advance industry-standard software engineering practices, including automation, observability, scalability, and MLOps, to deliver clean, maintainable, and testable code.
About You
Bachelor's degree in Computer Science, Engineering, or a related technical field.
8 or more years of experience in production-level Software Development.
4 or more years of experience in Python, with a consistent track record of shipping production code and systems.
4 or more years of experience building scalable data pipelines and working with large-scale datasets.
4 or more years of proven experience deploying production services to cloud platforms (e.g., AWS, Azure, GCP) and using containerization technologies (e.g., Docker, Kubernetes) for MLOps.
Other Qualifications:
MS/PhD degree in a relevant field, such as Computer Science or Engineering.
Deep technical expertise in the engineering, deployment, and MLOps of advanced machine learning solutions (e.g., generative models, LLMs, RAG, and AI agents), coupled with a strong understanding of scalable distributed systems, performance optimization, database technologies (e.g., PostgreSQL, Redis), and robust API development.
Proven algorithmic thinking and a tracproven historydesigning, implementing, and analyzing efficient algorithms for complex problems.
Demonstrated ability to build flexible, reusable, and well-documented software components, with comprehensive experience in code testing strategies (unit, integration, end-to-end) in a continuous deployment environment. Strong sense of ownership and a proven ability to deliver high-quality, finished products efficiently.
Excellent communication and collaboration skills, emphasizing team collaboration, knowledge-sharing, and delivering customer impact.
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.CO.Boulder
The application deadline for this role is the same as the posting end date stated as below:
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.
Pursuant to applicable Fair Chance law, Workday will consider for employment qualified applicants with arrest and conviction records.
Workday is an Equal Opportunity Employer including individuals with disabilities and protected veterans.
Are you being referred to one of our roles? If so, ask your connection at Workday about our Employee Referral process!
