Principal Software Development Engineer, MLOps

Your work days are brighter here. We’re obsessed with making hard work pay off, for our people, our customers, and the world around us. As a Fortune 500 company and a leading AI platform for managing people, money, and agents, we’re shaping the future of work so teams can reach their potential and focus on what matters most.

The minute you join, you’ll feel it. Not just in the products we build, but in how we show up for each other. Our culture is rooted in integrity, empathy, and shared enthusiasm.

We’re in this together, tackling big challenges with bold ideas and genuine care. We look for curious minds and courageous collaborators who bring sun-drenched optimism and drive. Whether you're building smarter solutions, supporting customers, or creating a space where everyone belongs, you’ll do meaningful work with Workmates who’ve got your back.

In return, we’ll give you the trust to take risks, the tools to grow, the skills to develop and the support of a company invested in you for the long haul. So, if you want to inspire a brighter work day for everyone, including yourself, you’ve found a match in Workday, and we hope to be a match for you too. 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 Principal 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, Go, 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.

Build an MLOps platform primarily using Kubeflow, Kubernetes, and other ML ecosystem tools for a unified ML development experience. Proficiency with Python, Go, and infrastructure-as-code tools like Terraform. Effectively engage with data scientists, ML engineers, PMs, and architects in requirements elaboration and drive technical solutions.

Own and develop cloud-based services end-to-end, including infrastructure as code. Design and build software solutions for efficient organization, storage, and retrieval of data to enable substantial scale. Apply cloud engineering and security best practices to build robust, scalable ML infrastructure.

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.

Understand agentic AI systems; familiarity with LangChain and LangSmith is preferred. About You Basic Qualifications 6 or more years of validated industry experience. Bachelor’s and/or Master’s degree in Computer Science or Computer Engineering.

Strong software engineering experience with designing and building scalable AI/ML platforms. Proficiency with Python, Go, and infrastructure-as-code tools like Terraform Design, implement, and maintain robust MLOps services for deploying, monitoring, and scaling ML and data engineering pipelines, primarily with Kubeflow. Deep understanding of cloud computing, cloud infrastructure, and distributed systems; experience with AWS and GCP.

Experience developing microservices, APIs, and large-scale web applications. Proficiency with Python, Go, and infrastructure-as-code tools like Terraform. Experience running and maintaining Kubernetes clusters in production.

Understanding of agentic AI concepts; experience with LangChain and LangSmith is preferred. Stay abreast of industry trends and emerging technologies, providing recommendations for continuous improvement of DevOps and machine learning practices. Troubleshoot and resolve performance bottlenecks, system outages, and operational issues collaboratively with ML teams.

Implement and manage CI/CD workflows to automate testing, integration, and delivery of ML components. Ensure security and compliance of AI platforms, implementing best practices for encryption, data protection, and access control. Other Qualifications Implementation and operation of distributed systems.

Experience with large-scale ML data pipelines and data lakes; familiarity with Databricks, Sagemaker, or Spark as a service. Ability to think across layers of the ML stack, from infrastructure to model deployment. Experience developing monitoring and alerting systems for ML infrastructure.

Proven leadership or mentoring experience. Workday Pay Transparency Statement T he 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: CAN.ON.Toronto Primary CAN Base Pay Range: $168,000 - $252,000 CAD Additional CAN Location(s) Base Pay Range: $168,000 - $252,000 CAD 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. At Workday, we are committed to providing an accessible and inclusive hiring experience where all candidates can fully demonstrate their skills.

If you require assistance or an accommodation at any point, please email accommodations@workday.com . Are you being referred to one of our roles? If so, ask your connection at Workday about our Employee Referral process!

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