Back to jobs

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

USA.VA.Reston

Pay
Multiple pay statements — pay source
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
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 Work
Read the full posting
Work setting
Not stated
Employment
Full-time — employment source
Employment type in the employer’s posting: Full Time
From the employer’s posting
Apply at Workday

What you’ll work on

Full posting

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.

  • Build frameworks, automation, and tooling for ML runtime inference applications

  • Deploy and orchestrate containers in production, including Kubernetes and ArgoCD

  • Own features end to end, including infrastructure as code

  • Build products that let developers work with the ML platform more easily

  • Take part in on-call support on a rotating basis

From the employer’s posting
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.
Deploying and orchestrating containers in production environments, including technologies like Containers, Kubernetes, Service Mesh, ArgoCD and related tools.
Own and develop features from end to end including infrastructure as code.
Developing products and services that empower developers to streamline their interactions with the ML platform.
Availability for on-call support on a rotational basis.

What you’ll bring

All qualifications

Core experience

  • 7+ years of professional experience in DevOps engineering, infrastructure automation, and CI/CD pipeline development.
  • Leadership & Operations: Proven experience leading technical initiatives and mentoring team members; willingness to participate in a rotating on-call schedule.
  • 7+ years of experience with Python programming and container orchestration platforms (e.g., Docker, Kubernetes).
  • 5+ years of professional DevOps experience, including infrastructure automation and CI/CD pipeline development.
  • Bachelor’s degree in Computer Science, STEM field, or equivalent practical experience.
  • 5+ years of experience with Python programming and containerization technologies (e.g., Docker, Kubernetes).
Qualification wording
7+ years of professional experience in DevOps engineering, infrastructure automation, and CI/CD pipeline development.
Leadership & Operations: Proven experience leading technical initiatives and mentoring team members; willingness to participate in a rotating on-call schedule.
7+ years of experience with Python programming and container orchestration platforms (e.g., Docker, Kubernetes).
5+ years of professional DevOps experience, including infrastructure automation and CI/CD pipeline development.
Bachelor’s degree in Computer Science, STEM field, or equivalent practical experience.
5+ years of experience with Python programming and containerization technologies (e.g., Docker, Kubernetes).
Education & alternatives
- 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
- 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:

Tools in this posting

  • Python
  • AWS
  • Docker
  • GCP
  • Grafana
  • Kubernetes
  • Terraform
Source — Tool mentions in context
- 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.
- 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.
- 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.
- 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.
- 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).
- 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.
- 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.
- 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.
- 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.

Posting record

Report an error
Status in our records
Live
First seen by us
Sep 24, 2026 · 35 days ago
Recorded sightings
113
Last seen by us
Oct 30, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

Your next step

  • Have your resume and examples of relevant work ready.
  • Check the listed location, eligibility and core experience before starting.

Complete your application on workday.wd5.myworkdayjobs.com. The employer’s form will show what is required.

Already applied? Track this application

Job description

View original posting ↗

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

Your work matters here. At Workday Government, we focus on outcomes that serve a larger mission. Our work supports U.S. federal agencies as they modernize and transform the full employee lifecycle experience and finance operations—so they can operate with greater clarity, accountability, and trust. As a Fortune 500 company and a proven enterprise cloud platform, Workday brings modern technology, responsible AI, and secure infrastructure to some of the most complex environments in the world. The work isn’t theoretical. It’s operational. It’s high-impact. And it demands rigor, integrity, and long-term thinking.

From day one, you’ll be part of a team that values collaboration, follow-through, and doing the right thing—especially when the stakes are high. Our culture is grounded in integrity, respect, and shared responsibility. We challenge each other to think clearly, act thoughtfully, and build solutions that stand up to real-world demands. Here, curiosity is matched with accountability. Ambition is paired with trust. You’ll have the space to do your best work, the support to keep growing, and the backing of a company committed to long-term investment in both its people and the federal mission.

If you’re looking to apply your experience to meaningful, mission-driven work—alongside colleagues who take pride in building things that last—you’ll find that opportunity at Workday Government.

About the Role

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.


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 You

This 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 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.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 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.


Workday is committed to providing reasonable accommodations for qualified individuals during our application process, in order to perform one or more essential functions of their job, as well as regarding the use of AI tools for employment decision-making to any degree. Please see below for more details including how to request an accommodation as a qualified veteran, due to a disability or for religious reasons, or as otherwise provided under applicable law.


Workday prohibits taking adverse action against any candidate or employee for reporting a possible violation of this policy, requesting one or more work accommodations, exercising a privacy right, or cooperating in an investigation in accordance with applicable law. Any employee who retaliates against a candidate or employee for doing so may be subject to disciplinary action, up to and including termination of employment, to the fullest extent allowable under applicable law.


If you require a reasonable accommodation, you may email accommodations@workday.com, as far in advance as possible.


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

At Workday, we value our candidates’ privacy and data security.  Workday will never ask candidates to apply to jobs through websites that are not Workday Careers. 

  

Please be aware of sites that may ask for you to input your data in connection with a job posting that appears to be from Workday but is not.

  

In addition, Workday will never ask candidates to pay a recruiting fee, or pay for consulting or coaching services, in order to apply for a job at Workday.

Source details

View original posting ↗

Source notes

Source excerpts

Selected passages from the saved posting. Check the full description for conditions and exceptions.

Pay
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
More source context
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 Work
Location & working pattern

USA.VA.Reston

About the Role 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.
More source context
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.
Work authorization
- 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 You This 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)

See how this role fits your experience

Add your resume to compare the role’s scope, tools and requirements with your experience.

Find answers in the posting

AI
How answers work

AI selects complete passages from this posting. Check them for conditions and exceptions.

Uses this posting and your question. No profile needed.