AI / ML Engineer Manager
Arlington, VA
- Pay
USD 126,300–243,100/yearAnnual period assumed — pay source
The pay range for the states of California, Colorado, Connecticut, Hawaii, Illinois, Maine, Maryland, Massachusetts, Minnesota, New Jersey, New York, Ohio, Vermont, Virginia, Washington, and the District of Columbia is: $126,300—$243,100 USD What We Believe
Read the full posting- Work setup
- Unconfirmed
- Employment
- Unconfirmed
Before you apply
- Sponsorship
Visa sponsorship not confirmed — sponsorship source
Applicants for employment in the US must have work authorization that does not now or in the future require sponsorship of a visa for employment authorization in the United States.
Read the full posting
What you’ll work on
Full postingLead, mentor, and manage a high-performing team of ML modeling developers and MLOps engineers.
Define and execute the technical strategy for the MaaS platform, including the frameworks for model training, versioning, deployment, and monitoring.
Oversee the design, development, and deployment of a diverse portfolio of machine learning models to solve complex mission challenges.
From the employer’s posting
Responsibilities: Lead, mentor, and manage a high-performing team of ML modeling developers and MLOps engineers. Define and execute the technical strategy for the MaaS platform, including the frameworks for model training, versioning, deployment, and monitoring.
Lead, mentor, and manage a high-performing team of ML modeling developers and MLOps engineers. Define and execute the technical strategy for the MaaS platform, including the frameworks for model training, versioning, deployment, and monitoring. Oversee the design, development, and deployment of a diverse portfolio of machine learning models to solve complex mission challenges.
Define and execute the technical strategy for the MaaS platform, including the frameworks for model training, versioning, deployment, and monitoring. Oversee the design, development, and deployment of a diverse portfolio of machine learning models to solve complex mission challenges. Establish and enforce robust MLOps practices to ensure automated, reliable, and scalable CI/CD pipelines for machine learning models.
What you’ll bring
All qualificationsCore experience
- 8+ years of experience in data science or machine learning engineering, with at least 3 years in a technical leadership or management role.
- Deep expertise in developing and deploying ML models using common frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
- Proven experience building and maintaining production ML systems in a cloud environment (AWS, Azure, GCP).
- Strong understanding of MLOps principles and hands-on experience with relevant tools (e.g., MLflow, Kubeflow, AWS SageMaker, Azure ML).
- Proficiency with containerization technologies (Docker, Kubernetes) and CI/CD tools.
- Experience with programming skills in Python and familiarity with software engineering best practices.
Preferred experience
- Experience with ML platforms like Databricks or AWS SageMaker AI.
- Familiarity with Infrastructure-as-Code (IaC) tools like Terraform.
- Experience working in a high-security DoD or Intelligence Community environment.
Qualification wording
8+ years of experience in data science or machine learning engineering, with at least 3 years in a technical leadership or management role.
Deep expertise in developing and deploying ML models using common frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
Proven experience building and maintaining production ML systems in a cloud environment (AWS, Azure, GCP).
Strong understanding of MLOps principles and hands-on experience with relevant tools (e.g., MLflow, Kubeflow, AWS SageMaker, Azure ML).
Proficiency with containerization technologies (Docker, Kubernetes) and CI/CD tools.
Experience with programming skills in Python and familiarity with software engineering best practices.
Experience with ML platforms like Databricks or AWS SageMaker AI.
Familiarity with Infrastructure-as-Code (IaC) tools like Terraform.
Experience working in a high-security DoD or Intelligence Community environment.
Tools in this posting
- Python
- AWS
- Azure
- Databricks
- Docker
- Kubernetes
- MLflow
- SageMaker
- PyTorch
- TensorFlow
- Google Cloud (GCP)
- Terraform
- scikit-learn
Source — Tool mentions in context
- Proficiency with containerization technologies (Docker, Kubernetes) and CI/CD tools. - Experience with programming skills in Python and familiarity with software engineering best practices. - US Citizenship (No Dual Citizenship)
- Deep expertise in developing and deploying ML models using common frameworks (e.g., TensorFlow, PyTorch, scikit-learn). - Proven experience building and maintaining production ML systems in a cloud environment (AWS, Azure, GCP). - Strong understanding of MLOps principles and hands-on experience with relevant tools (e.g., MLflow, Kubeflow, AWS SageMaker, Azure ML).
- Proven experience building and maintaining production ML systems in a cloud environment (AWS, Azure, GCP). - Strong understanding of MLOps principles and hands-on experience with relevant tools (e.g., MLflow, Kubeflow, AWS SageMaker, Azure ML). - Proficiency with containerization technologies (Docker, Kubernetes) and CI/CD tools.
- Direct experience building a Model-as-a-Service or Machine-Learning-as-a-Service platform. - Experience with ML platforms like Databricks or AWS SageMaker AI. - Familiarity with Infrastructure-as-Code (IaC) tools like Terraform.
- Strong understanding of MLOps principles and hands-on experience with relevant tools (e.g., MLflow, Kubeflow, AWS SageMaker, Azure ML). - Proficiency with containerization technologies (Docker, Kubernetes) and CI/CD tools. - Experience with programming skills in Python and familiarity with software engineering best practices.
- 8+ years of experience in data science or machine learning engineering, with at least 3 years in a technical leadership or management role. - Deep expertise in developing and deploying ML models using common frameworks (e.g., TensorFlow, PyTorch, scikit-learn). - Proven experience building and maintaining production ML systems in a cloud environment (AWS, Azure, GCP).
- Experience with ML platforms like Databricks or AWS SageMaker AI. - Familiarity with Infrastructure-as-Code (IaC) tools like Terraform. - Experience working in a high-security DoD or Intelligence Community environment.
Job description
At Accenture Federal Services, nothing matters more than helping the US federal government make the nation stronger and safer and life better for people. Our 13,000+ people are united in a shared purpose to pursue the limitless potential of technology and ingenuity for clients across defense, national security, public safety, civilian, and military health organizations.
Join Accenture Federal Services, a technology company within global Accenture. Recognized as a Glassdoor Top 100 Best Place to Work, we offer a collaborative and caring community where you feel like you belong and are empowered to grow, learn and thrive through hands-on experience, certifications, industry training and more.
Join us to drive positive, lasting change that moves missions and the government forward!
As the Manager for the AI/ML Models as a Service (MaaS) team, you will lead a specialized group of developers and engineers dedicated to productionizing machine learning for the DoD. Your mission is to build and manage a centralized platform that provides access to pre-trained and custom-built AI/ML models, simplifying their integration and accelerating the delivery of AI-powered capabilities across the enterprise . This is a strategic, hands-on leadership role where you will define the vision for our MaaS offerings and oversee the entire lifecycle of model development, deployment, and operations.
Responsibilities:
- Lead, mentor, and manage a high-performing team of ML modeling developers and MLOps engineers.
- Define and execute the technical strategy for the MaaS platform, including the frameworks for model training, versioning, deployment, and monitoring.
- Oversee the design, development, and deployment of a diverse portfolio of machine learning models to solve complex mission challenges.
- Establish and enforce robust MLOps practices to ensure automated, reliable, and scalable CI/CD pipelines for machine learning models.
- Architect the service layer for the MaaS platform, ensuring models are exposed via secure, scalable, and well-documented APIs.
- Collaborate with data scientists, data engineers, and mission stakeholders to identify use cases and translate requirements into production-ready models.
- Implement governance, security, and ethical AI standards across the entire model lifecycle.
- Manage project timelines, resource allocation, and stakeholder communication for all MaaS initiatives.
Required Qualifications:
- 8+ years of experience in data science or machine learning engineering, with at least 3 years in a technical leadership or management role.
- Deep expertise in developing and deploying ML models using common frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
- Proven experience building and maintaining production ML systems in a cloud environment (AWS, Azure, GCP).
- Strong understanding of MLOps principles and hands-on experience with relevant tools (e.g., MLflow, Kubeflow, AWS SageMaker, Azure ML).
- Proficiency with containerization technologies (Docker, Kubernetes) and CI/CD tools.
- Experience with programming skills in Python and familiarity with software engineering best practices.
- US Citizenship (No Dual Citizenship)
Preferred Qualifications:
- Direct experience building a Model-as-a-Service or Machine-Learning-as-a-Service platform.
- Experience with ML platforms like Databricks or AWS SageMaker AI.
- Familiarity with Infrastructure-as-Code (IaC) tools like Terraform.
- Experience working in a high-security DoD or Intelligence Community environment.
- Demonstrated success leading teams that deliver complex, data-driven software projects.
Security Clearance:
- Active TS or TS/SCI Clearance
As required by local law, Accenture Federal Services provides reasonable ranges of compensation for hired roles based on labor costs in the states of California, Colorado, Connecticut, Hawaii, Illinois, Maine, Maryland, Massachusetts, Minnesota, New Jersey, New York, Ohio, Vermont, Virginia, Washington, and the District of Columbia. The base pay range for this position in these locations is shown below. Compensation for roles at Accenture Federal Services varies depending on a wide array of factors, including but not limited to office location, role, skill set, and level of experience. Accenture Federal Services offers a wide variety of benefits. You can find more information on benefits here. We accept applications on an on-going basis and there is no fixed deadline to apply.
The pay range for the states of California, Colorado, Connecticut, Hawaii, Illinois, Maine, Maryland, Massachusetts, Minnesota, New Jersey, New York, Ohio, Vermont, Virginia, Washington, and the District of Columbia is:
$126,300—$243,100 USD
What We Believe
As a company wholly dedicated to serving the US federal government, we bring together the best talent to help reinvent how federal agencies operate and deliver greater value for their mission and the American people. We have an unwavering commitment to creating a culture in which all our people are respected, feel a sense of belonging, and have equal opportunity. As a business imperative, every person at Accenture Federal Services has the responsibility to create and sustain a culture where everyone feels welcomed and included. This is grounded in our core values and our experience that hiring and developing great people who reflect different perspectives, experiences, and backgrounds is key to driving innovation and delivering the results that our clients and the country count on.
Equal Employment Opportunity Statement
We believe that no one should be discriminated against because of their differences. All employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other basis as protected by federal, state, or local law. Our rich diversity makes us more innovative, more competitive, and more creative, which helps us better serve our clients and our communities. For details, view a copy of the Accenture Federal Services Equal Opportunity Policy Statement.
Accenture Federal Services is an Equal Employment Opportunity employer. Additionally, as an Affirmative Action Employer for Veterans and Individuals with Disabilities, Accenture Federal Services is committed to providing veteran employment opportunities to our service men and women.
Requesting An Accommodation
Accenture Federal Services is committed to providing equal employment opportunities for persons with disabilities or religious observances, including reasonable accommodation when needed. If you are hired by Accenture Federal Services and require accommodation to perform the essential functions of your role, you will be asked to participate in our reasonable accommodation process. Accommodations made to facilitate the recruiting process are not a guarantee of future or continued accommodations once hired.
If you are being considered for employment opportunities with Accenture Federal Services and need an accommodation for a disability or religious observance during the interview process or for the job you are interviewing for, please speak with your recruiter.
Other Employment Statements
Applicants for employment in the US must have work authorization that does not now or in the future require sponsorship of a visa for employment authorization in the United States.
Candidates who are currently employed by a client of Accenture Federal Services or an affiliated Accenture business may not be eligible for consideration.
Job candidates will not be obligated to disclose sealed or expunged records of conviction or arrest as part of the hiring process.
The Company will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. Additionally, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, or (c) consistent with the Company's legal duty to furnish information.
California requires additional notifications for applicants and employees. If you are a California resident, live in or plan to work from Los Angeles County upon being hired for this position, please click here for additional important information.
Your next step
- Have your CV and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
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Source & posting history
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
The pay range for the states of California, Colorado, Connecticut, Hawaii, Illinois, Maine, Maryland, Massachusetts, Minnesota, New Jersey, New York, Ohio, Vermont, Virginia, Washington, and the District of Columbia is: $126,300—$243,100 USD What We Believe
- Location & working pattern
Arlington, VA
Working pattern and location restrictions need checking in the full posting.
- Work authorization
- Experience with programming skills in Python and familiarity with software engineering best practices. - US Citizenship (No Dual Citizenship) Preferred Qualifications:
More source context
- Demonstrated success leading teams that deliver complex, data-driven software projects. Security Clearance: - Active TS or TS/SCI Clearance
More relevant text appears in the full description.
- Status in our records
- Active
- First seen by us
- Mar 21, 2026
- Recorded sightings
- 246
- Last seen by us
- Oct 7, 2026
These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.
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