Intermediate MLOps Engineer - US Federal

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

This is an opportunity to be part of a growth team focused on MLOps. We build ML capabilities into our products, and you would be building part of the next generation of Workday technology. We believe predictive products can be as ground-breaking to the next generation of technology as mobile was to the last.

As a Software Engineer you will help develop ML powered features and experiences for every user across our HR & Talent product portfolio. You will work closely with ML engineers and other software teams to deliver critically important infrastructure and software frameworks that enable machine learning across Workday's product ecosystem. You will apply modern MLOps, CloudOps, and data engineering stacks to enable development, training, deployment, and lifecycle management of a variety of ML capabilities; supervised and unsupervised, deep learning and classical. You will be responsible for the design & development of new APIs/microservices and deploy them using Python, Terraform and Kubernetes at scale.

You will use Workday's vast computing resources on rich, exclusive datasets to deliver value that transforms the way our end-users experience WD. We will challenge you to apply your best creative thinking, analysis, problem-solving, and technical abilities to make an impact on thousands of enterprises and millions of people.

About the Role

In this role, you would:

• Work with multi-functional teams to deliver scalable, secure and reliable solutions.
• Building MLOps platform primarily using Kubeflow, and other ML ecosystem tools and services for a unified ML Development experience.
• Successfully communicate with data scientists, ML engineers, PMs and architects in requirements elaboration and drive technical solutions.
• Own and develop cloud based services from end to end including infrastructure as code.
• Design and build software solutions for efficient organization, storage and retrieval of data to enable substantial scale.
• Understanding cloud computing and security to build robust cloud infrastructure and solutions for ML teams.
• Build systems and dashboards to monitor service & ML health.
• Lead in architecture reviews, code reviews and technology evaluation.
• Research, evaluate, prototype and drive adoption of new ML tools with reliability and scale in mind.

About You

Basic Qualifications for Software Engineer

• US Citizenship required
• 3 or more years of validated industry experience.
• Bachelor's and/or Master's degree in Computer Science or Computer Engineering.
• Design, implement, and maintain robust MLOps services for deploying, monitoring, and scaling machine learning development and data engineering primarily with Kubeflow.
• Stay abreast of industry trends and emerging technologies, providing recommendations for continuous improvement of our DevOps and machine learning practices.
• Fix and resolve performance bottlenecks, system outages, and other operational issues in collaboration with the ML engineering teams.
• Optimize public cloud-based infrastructure (AWS, GCP) to support the computational requirements of machine learning workloads.
• Implement and manage CI/CD workflows to automate testing, integration, and delivery of machine learning components.
• Ensure the security and compliance of machine learning platforms, implementing standard methodologies for encryption, data protection and access controls.
• Professional experience in building web applications and microservices and API design.
• Experience in supporting large Kubernetes networks in production.
• 3 or more years of cloud programming experience preferably in Python or Go.
• Experience with running and maintaining Databricks, Sagemaker, & Apache Spark as a service.

Other Qualifications

• Implementation and operation of distributed systems and software development including the conception, specifying, designing, programming, documenting, testing, and bug fixing involved in creating and maintaining applications, frameworks, or other software components.
• Experience in managing relevant tools like Databricks and Sagemaker to perform efficient computation and management of large scale data lakes.
• Experience of data and/or ML systems with ability to think across layers of the stack.
• Develop and maintain monitoring and alerting systems for proactively identifying and addressing issues within the machine learning infrastructure.
• Experience in leading or mentoring other team members and proven team teamwork experience, i.e. understanding group dynamics, effective communication strategies, conflict resolution techniques, and the ability to foster a positive and inclusive team environment

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

Primary Location Base Pay Range: $128,800 USD - $193,200 USD

Additional US Location(s) Base Pay Range: $122,400 USD - $217,200 USD

Additional Considerations:

The application deadline for this role is the same as the posting end date stated as below:

08/19/2025

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.

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