ML Engineering - ML Ops

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

Workday was founded on a vision to revolutionize enterprise software, built on a culture that puts people first. Our success is driven by a collaborative, employee-centric environment, where Workmates thrive and contribute to a greater purpose. We prioritize our people, communities, and the planet while maintaining profitability. Here, you’re encouraged to be yourself, embrace your energy and passion, and help shape the future. Join us in creating a brighter Workday for all!

Come join the Workday Search/Assistant team! We are part of the Employee Experience organization that enables employers to better engage and support their people while making work more personal and productive.

Workday is looking for a hardworking Machine Learning Operations engineer to contribute to the strategic mission of reaching workers where they are at. You will join an energetic, open minded and supportive group of engineers to redefine how workers engage with Enterprise applications. If you have a willingness to explore the unknown, be a technological pioneer and have passion around improving customer experiences then we want to hear from you!

About the Role

As a machine learning engineer passionate about ML Ops, you will

• Implement MLOps tools, frameworks, and platforms to support ML development, deployment, and governance

• Create and maintain a repeatable and reusable ML workflow for model training, evaluation, deployment, and maintenance

• Improve tracking and monitoring of models, experiments, artifacts, and data

• Engage with data engineers and data scientists in feature engineering efforts

• Diagnose and resolve ML workflow and production issues quickly

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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 You

• Highly self-motivated, always looking to take on work and get great pleasure from delivering production scale machine learning solutions to customers

• A collaborative teammate who uses positive leadership to coordinate and deliver results across teams

• A fast learner, detail oriented, decisive, and enjoys a fast-paced work environment

• Flexible, reliable, outgoing and has a positive work attitude.

Basic Qualifications

• 3+ years understanding of Python in both production and ETL settings

• 2+ years of building Data or MLOps pipelines using Python, Airflow, Databricks, or other similar cloud native services

• 2+ years experience on AWS, Vertex AI, and Kubernetes 

• 2+ years experience in operationalization of Data Science projects using at least one of the popular frameworks or platforms (e.g. Airflow, Kubeflow, AWS Sagemaker, Google AI Platform) - Kubeflow in particular is a plus

• 1+ years experience building both data / ETL pipelines as well as model training infrastructure, and working with GPUs

• 1+ years Experience managing and supporting Docker, Kubernetes, Spark, CI/CD, Git-Ops

• 1+ years Experience with data versioning, ML model management, lifecycle, and reproducibility

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Other Qualifications

• Experience with ML frameworks such as PyTorch, Keras, Transformers, SKLearn

• Experience with fine-tuning NLP models and with HuggingFace

• Experience with AWS services especially EKS  

• 1+ years with MLOps tools like TFX, MLFlow, Kubeflow, Apache Spark, etc.

• B.S. in a relevant field - (E.g. Computer Science, Mathematics, Engineering). M.S. or Ph.D are nice, but not required

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: $147,200 USD - $220,800 USD

 

Additional US Location(s) Base Pay Range: $139,800 USD - $248,400 USD

If performed in Colorado, the pay range for this job is $147,200 - $220,800 USD based on min and max pay range for that role if performed in CO.

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

06/30/2025

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.

Are you being referred to one of our roles? If so, ask your connection at Workday about our Employee Referral process!