About the RoleEmployees 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.
Key Responsibilities:- 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.
This role will support one or more direct or indirect contracts with the U.S. Federal Government which, due to federal government security requirements, mandates that all Workday personnel working on the contracts be United States citizens (naturalized or native).About YouThis role may require a security clearance at the TS/SCI w/CI Poly level. Applicants must have the ability to obtain and maintain a U.S. government issued security clearance. An active TS/SCI w/CI Poly is preferred.Basic Qualifications (P4 Sr. SDE)- 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.
Other / Preferred Qualifications- 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.
Basic Qualification (P3 SDE)- 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.
Other Qualifications:- 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.
Workday Pay Transparency StatementThe 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.VA.Reston
Primary Location Base Pay Range: $163,800 USD - $245,800 USD
Additional US Location(s) Base Pay Range: $148,200 USD - $264,000 USD
Our Approach to Flexible WorkWith 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.
