Dark Wolf Solutions is seeking an ML Ops Engineer to support a team responsible for developing, integrating, and maintaining the NRO’s Clairvoyant Framework on Unclassified, Secret, and  Top-Secret SCI domains, including development, test, and operational environments. This role focuses on the operationalization of machine learning models and analytics within this framework.

Responsibilities:

• Implementing and maintaining robust, secure pipelines for migrating machine learning models and applications across unclassified, secret, and top-secret cloud environments, including hybrid cloud operations and API  management for ML services. 
• Applying data-centric, robust, modular, and  loosely coupled design principles, utilizing Open Systems Architectures (OSA) and  Microservices Architectures (MSA), to optimize cloud resource use for ML workloads. 
• Contributing to and support an agile software  development environment by implementing configuration management, continuous  integration (CI) for models, automation scripts, container technologies (e.g., Docker,  Kubernetes) for ML deployment, and managing source code and issue tracking systems,  with specific attention to Multi-INT Makerspace maintenance. 
• Delivering technical operations  support for the ML DevOps Pipeline, including infrastructure (e.g., C2S), security  compliance, data integration for ML processes, and collaborating on the transition of ML  applications and analytics from test to live operations.

Required Qualifications:

• Bachelor’s degree in Computer Science, Software Engineering, Information  Technology, or a related technical field. 
• Minimum of 2 years of experience in software engineering, systems engineering, or related IT systems development, with a specific focus on MLOps practices,  machine learning engineering, or cloud infrastructure supporting ML workloads.
• Demonstrated experience in implementing and maintaining CI/CD pipelines.
• Hands-on experience with cloud computing platforms, particularly AWS services  (e.g., EC2, S3, ECS, Lambda, CloudFormation), including AWS SageMaker.
• Proficiency with containerization technologies (e.g., Docker, Kubernetes). 
• Experience with configuration management tools (e.g., Ansible, Puppet, Chef).
• Experience with scripting languages (e.g., Python, Bash) for automation.
• Familiarity with source code management tools (e.g., Git, GitLab, GitHub) and  issue tracking systems (e.g., Jira, Bitbucket). 
• Understanding of microservices architecture principles, including modularity, loose coupling, and bounded context.
• Experience with MLOps platforms and concepts, including model versioning,  experiment tracking, and data versioning. 
• Ability to work in an Agile development environment, participating in  sprint/release planning and backlog grooming. 
• US Citizenship and an active Top Secret security clearance with SCI eligibility and a successfully completed Counterintelligence Polygraph.

Desired Qualifications:

• Experience with Amazon SC2S and C2S environments.
• Familiarity with the I2SPO Multi-INT Makerspace (M2) or SageMakerSpace.
• Prior experience supporting NRO or other Intelligence Community (IC) missions.
• Experience contributing to or publishing developed source code for Framework Services to common repositories.
• Participation in IC activities to improve and advance DevOps tools and processes.
• Knowledge of specific IC or DoD security standards and directives (e.g., ICD 503, NIST SP 800 series).

This position is located in Chantilly, VA.