AI / ML Engineer Manager

AI / ML Engineer Manager Arlington, VA 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 The pay range for the states of California, Colorado, Hawaii, Illinois, Maine, Maryland, Massachusetts, Minnesota, New Jersey, New York, Vermont, Virginia, Washington, and the District of Columbia, and the city of Cleveland is: $126,300 - $243,100 USD Accenture Federal Services