Mid / Senior Software Development Engineer - ML Ops (US Federal)

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.

Employees may be required to be on site at client locations in the DC, MD, and VA (DMV) area

The Workday ML Runtime team is seeking an energetic and determined Software Engineer to design, implement, and deliver highly scalable features for our Machine Learning Runtime platform. As a member of this fast paced group you will have a unique and rewarding opportunity to shape and contribute towards microservices that power Workday Machine Learning features in production. You will partner with Data Scientists, ML Engineers, and other Software Engineers to create the technology that brings these features to life.

• →Developing frameworks, automation, and tooling to foster a culture of efficiency and innovation.
• →Apply technologies like Kubernetes, Docker, and Python to enhance developer scalability in creating innovative ML Runtime Inference applications.
• →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.
• →Developing products and services that empower developers to streamline their interactions with the ML platform.
• →Working with public clouds (such as IAAS, AWS, GCP) and applying capacity management principles.
• →Deploying and orchestrating containers in production environments, including technologies like Containers, Kubernetes, Service Mesh, ArgoCD and related tools.
• →Actively engage with Tech Leads and ML Engineers across teams to elaborate on requirements and drive technical solutions.
• →Own and develop features from end to end including infrastructure as code.
• →Research, evaluate, prototype and drive adoption of new ML tools with reliability and scale in mind
• →Strong dedication to proactively addressing and resolving issues, automating processes, and empowering engineers to self-service their operational needs for improved productivity.
• →Availability for on-call support on a rotational basis.

• 7+ years of professional experience in DevOps engineering, infrastructure automation, and CI/CD pipeline development.
• 7+ years of experience with Python programming and container orchestration platforms (e.g., Docker, Kubernetes).
• Bachelor’s degree in Computer Science, STEM field, or equivalent practical experience.

• MLOps & Domain Experience: Hands-on experience designing, deploying, and scaling Machine Learning runtime platforms and inference pipelines in partnership with ML teams.
• Tooling & Infrastructure: Proficiency with Infrastructure as Code (e.g., Terraform), Git SCM workflows, and GitOps/CD engines (e.g., ArgoCD, Jenkins).
• Observability: Experience building end-to-end monitoring, metrics, and alerting pipelines using telemetry stacks like Grafana or Prometheus.
• Architecture & Code Quality: Strong understanding of distributed systems, SaaS microservices, Object-Oriented Design (OOD), and automated testing methodologies (unit, integration, e2e).
• Leadership & Operations: Proven experience leading technical initiatives and mentoring team members; willingness to participate in a rotating on-call schedule.

• 5+ years of professional DevOps experience, including infrastructure automation and CI/CD pipeline development.
• 5+ years of experience with Python programming and containerization technologies (e.g., Docker, Kubernetes).
• Bachelor’s degree in Computer Science, STEM field, or equivalent practical experience.

• MLOps Experience: Hands-on experience deploying, monitoring, and scaling Machine Learning runtime environments or pipelines alongside ML teams.
• Tooling & Infrastructure: Experience with Infrastructure as Code (e.g., Terraform), Git workflows, and GitOps/CD engines (e.g., ArgoCD, Jenkins).
• Observability: Experience building monitoring, metrics, and alerting systems using telemetry stacks such as Grafana or Prometheus.
• Software Fundamentals: Solid understanding of Object-Oriented Design (OOD), distributed systems, and SaaS microservice architectures.
• Quality & Operations: Familiarity with automated testing frameworks (unit, integration, e2e) and willingness to participate in a rotating on-call schedule.

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.

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