AI / ML Engineer Manager

<div class="content-intro"><div> <div> </div> <div>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. </div> <div> </div> <div>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. </div> <div> </div> <div>Join us to drive positive, lasting change that moves missions and the government forward!</div> <div> </div> </div></div><p>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.</p> <p><strong>Responsibilities: </strong></p> <ul> <li>Lead, mentor, and manage a high-performing team of ML modeling developers and MLOps engineers.</li> <li>Define and execute the technical strategy for the MaaS platform, including the frameworks for model training, versioning, deployment, and monitoring.</li> <li>Oversee the design, development, and deployment of a diverse portfolio of machine learning models to solve complex mission challenges.</li> <li>Establish and enforce robust MLOps practices to ensure automated, reliable, and scalable CI/CD pipelines for machine learning models.</li> <li>Architect the service layer for the MaaS platform, ensuring models are exposed via secure, scalable, and well-documented APIs.</li> <li>Collaborate with data scientists, data engineers, and mission stakeholders to identify use cases and translate requirements into production-ready models.</li> <li>Implement governance, security, and ethical AI standards across the entire model lifecycle.</li> <li>Manage project timelines, resource allocation, and stakeholder communication for all MaaS initiatives.</li> </ul> <p><strong>Required Qualifications: </strong></p> <ul> <li>8+ years of experience in data science or machine learning engineering, with at least 3 years in a technical leadership or management role.</li> <li>Deep expertise in developing and deploying ML models using common frameworks (e.g., TensorFlow, PyTorch, scikit-learn).</li> <li>Proven experience building and maintaining production ML systems in a cloud environment (AWS, Azure, GCP).</li> <li>Strong understanding of MLOps principles and hands-on experience with relevant tools (e.g., MLflow, Kubeflow, AWS SageMaker, Azure ML).</li> <li>Proficiency with containerization technologies (Docker, Kubernetes) and CI/CD tools.</li> <li>Experience with programming skills in Python and familiarity with software engineering best practices. </li> <li>US Citizenship (No Dual Citizenship)</li> </ul> <p><strong>Preferred Qualifications: </strong></p> <ul> <