Senior MLOps Engineer

This Department of War enterprise data and analytics program delivers mission-critical capabilities that enable leaders across the Department to make faster better-informed decisions using trusted data at scale. Leidos Digital Modernization sector is seeking an experiencedSeniorMLOpsEngineerto support the delivery enhancement and adoption of enterprise data and analytics products used across multiple DoD organizations.

In this role you will work alongside government partners engineers and other industry teammates to translate operational and strategic requirements into scalable production-ready solutions. You will contribute directly to product planning execution and continuous improvementhelping ensure capabilities are delivered efficiently aligned to mission priorities and positioned for sustained success.

This position offers the opportunity to work on a high-visibility enterprise program at the intersection of data analytics and emerging AI technologies. Ideal candidates are motivated by mission impact comfortable operating in complex stakeholder environments and interested in building deep domainexpertisewhile delivering capabilities with real-world national security outcomes.

Primary Responsibilities:

• Design build andmaintainscalable machine learning pipelines for model deployment validation monitoring and lifecycle management.

• Implement model versioning drift detection and continuous retraining workflows to ensure model accuracy and compliance.

• Collaborate with data scientists platform engineers and security teams to ensure reliable secure and efficient delivery of AI/ML capabilities.

• Develop andmaintainsystems engineering and cybersecurity artifacts for the System.

• Preparemaintain and execute a System Engineering Plan (SEP) for managing all systems architecture and system engineering related aspects of the program.

• Conduct systems engineering activities required to specify build andmaintainsystem engineering designs for the System.

• Design engineer integrate and continuously improve the underlying infrastructure of the System including cloud environment network data storage logging and auditing functions.

• Define documentmaintain andpromulgateAPIs and technical standards for using and interoperating within and outside the System.

• Establish andmaintainintegrations with external model providers making their available models accessible via API.

• Provide Tier-4 support for any critical issues with the available services and productsin accordance withdefined SLAs.

• Design architect engineer and continuously improve all aspects of cybersecurity elements of the System.

• Perform site reliability engineering to build andmaintaina reliable scalable and efficient System by applying software engineering principles to operational tasks.

• Participate in the Engineering Control Board (ECB) process for supporting all major engineering milestones and decisions for the program.

Basic Qualifications:

• Bachelors degree in Computer Science Engineering or a related field.

• Minimum of 8 years of experience in machine learning operations (MLOps) or related fields.

• Experience with cloud platforms that host and manage infrastructuresuch as AWS Azure or Google Cloud.

• Proficiencyin programming languages such as Python Java or C.

• Experience with containerization and orchestration tools like Docker and Kubernetes.

• Strong understanding of machine learning model lifecycle management.

• Experience with CI/CD pipelines and version control systems like Git.

• Top Secret clearanceto start.

• Strong problem-solving skills and ability to work in a collaborative environment.

Preferred Qualifications:

• Masters degree in Computer Science Engineering or a related field.

• TS/SCI with CI Poly clearance.

• Experience with AI/ML frameworks such as TensorFlowPyTorch or scikit-learn.

• Familiarity with DoD standards referencedesigns and policy.

• Experience with cybersecurity practices and compliance.

• Knowledge ofDevSecOpspractices and tools.

• Experience with site reliability engineering (SRE) principles.

• Strong communicationand documentation skills.