ML Software Engineer Jobs in Virginia
ML Software Engineer jobs in Virginia are in high demand, with strong hiring concentrated in defense contracting, federal IT services, and commercial cloud infrastructure, drawing candidates from entry-level associate roles through principal and staff engineers. Northern Virginia anchors the market as one of the most active ml hiring corridors in the country, with Reston, McLean, and Arlington home to major employers including Leidos, Booz Allen Hamilton, and Amazon Web Services. The most sought-after specialties in Virginia listings are computer vision, natural language processing, and MLOps engineering. Find a role that fits below and apply directly.
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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.
See All 7 ML Software Engineer Jobs in Virginia
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Find ML Software Engineer JobsML Software Engineer Jobs by City in Virginia
Where Virginia roles are concentrated, by current openings.
ML Software Engineer Job Market in Virginia
A snapshot from current Virginia openings, updated as new roles post.
Who's Hiring



What Virginia Employers Look For
The qualifications that appear most often in ML software engineer jobs across Virginia.
- Bachelor's or master's degree in computer science, machine learning, or a closely related field
- Proficiency in Python and machine learning frameworks such as TensorFlow or PyTorch
- Experience designing, training, and deploying models in production environments
- Familiarity with cloud platforms, particularly AWS, Azure, or Google Cloud
- Active or obtainable U.S. security clearance, required by many Virginia defense contractors
- Strong understanding of MLOps practices including model monitoring, versioning, and CI/CD pipelines
ML Software Engineer Jobs in Virginia: Frequently Asked Questions
How do you become a ml software engineer in Virginia?
There is no state-issued license required to work as an ml software engineer in Virginia. The standard path is a bachelor's degree in computer science, data science, or a related field, followed by hands-on experience with machine learning frameworks and cloud platforms. Virginia's large defense and federal IT sector means that obtaining a security clearance early, often through an employer-sponsored investigation, significantly broadens the roles available to you.
How much do ML software engineers make in Virginia?
ML software engineers in Virginia earn a median of about $136,460 a year, based on May 2025 Bureau of Labor Statistics wage data, ranging from around $83,350 for the lowest 10% to over $211,930 for the top 10%. Pay rises with experience, specialty, and employer.
Which companies hire ml software engineers in Virginia?
Employers hiring ml software engineers in Virginia right now include Draper, HII, and TIAG, based on current listings on Migrate Mate as of September 2026. Virginia's concentration of defense primes, federal agencies, and hyperscale cloud infrastructure operators means hiring tends to be consistent across both commercial and government-adjacent roles.
Which Virginia cities have the most ml software engineer jobs?
The Virginia cities with the most ml software engineer openings are Reston, McLean, and Springfield. Northern Virginia dominates because it houses the headquarters or major campuses of leading defense contractors and is home to one of the world's largest data center clusters, which drives sustained demand from cloud and infrastructure teams operating out of Reston, McLean, and Arlington.
Are there remote ml software engineer jobs in Virginia?
Yes, and more than most fields. About 50% of ml software engineer openings tied to Virginia are remote or hybrid as of September 2026, reflecting how naturally this work adapts to distributed environments. Model development, experimentation, and data pipeline work are the portions most commonly done fully remote, while roles tied to classified government contracts typically require on-site presence.
How can I get hired as a ml software engineer in Virginia with little or no experience?
The most realistic entry path is through a junior or associate machine learning engineer role at a Virginia-based federal contractor or commercial tech firm. Booz Allen Hamilton and Leidos both run structured new-graduate programs and internship pipelines that convert into full-time positions. Building a portfolio of end-to-end projects on public datasets, earning a cloud certification from AWS or Google Cloud, and targeting roles titled 'associate data scientist' or 'junior ML engineer' are the credentials that move a resume past the screening stage.
Where can I find and apply to ml software engineer jobs in Virginia?
You can find and apply to ml software engineer jobs in Virginia on Migrate Mate, which lists current Virginia openings updated regularly. Find roles that match your experience and apply directly to the ones that fit.
See All 7 ML Software Engineer Jobs in Virginia
Find roles in Virginia that match your experience and apply in just a few clicks.
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