ML Ops Engineer - Clearance Required

LMI is seeking a Machine Learning Operations Engineer (ML Ops Engineer) to support the development of cutting-edge AI/ML solutions in collaboration with the Army’s AI2C organization. This role emphasizes integrating machine learning workflows into scalable applications while addressing operational needs for the United States Army.

Responsibilities:

• Build, train, validate, and evaluate machine learning models using technologies such as Scikit-Learn, TensorFlow, or similar tools
• Research, develop, and implement generative AI applications, ensuring that models address complex real-world challenges effectively
• Deploy machine learning models to web-based applications and integrate them into operational environments
• Operationalize generative AI systems by developing robust, scalable pipelines for deployment across multiple environments
• Design and implement advanced data manipulation and pipelining workflows using tools such as Pandas and PySpark to support model training and analysis
• Support CI/CD pipelines tailored for ML model development and deployment
• Work alongside other engineering and DevSecOps teams to support scalable cloud-based deployments
• Collaborate directly with Army stakeholders to identify strategic opportunities for ML integration, addressing challenges and providing innovative technical solutions
• Assist product leads in translating operational needs and feedback into actionable technical requirements and strategies
• Mentor junior team members, guiding their ML and MLOps skill development while contributing to process improvements
• Lead discussions on architecture, system design, technology adoption, and team development to strengthen LMI’s ML capabilities
• Build and maintain strong relationships with government customers and stakeholders through hybrid on-site engagement
• Contribute to technical narratives for proposals, white papers, and strategic documentation for expanding AI/ML and ML Ops projects within Army domains

Requirements:

• Bachelor's degree in Computer Science, Data Science, Software Engineering, or a related field
• 3+ years of experience in machine learning engineering, with particular emphasis on MLOps, model development, and deployment
• Demonstrated expertise in data manipulation & pipelining technologies, such as Pandas or PySpark
• Hands-on experience developing machine learning models using tools such as Scikit-Learn, MLlib, TensorFlow, PyTorch, etc
• Practical experience in deploying AI/ML models in production web-based applications
• Advanced proficiency with Python and Python-based web frameworks (e.g., Flask, Django, FastAPI, etc.)
• Strong understanding and hands-on experience with containerization technologies, such as Docker and Kubernetes
• Familiarity with Agile or Scrum methodologies, CI/CD practices, and version control systems (e.g., Git)
• Comfort operating in ambiguous and dynamic environments requiring proactive problem-solving
• Active Secret Clearance required
• Master's degree in Computer Science, Software Engineering, Information Systems, or related field
• 7+ years of directly related experience
• Proven track record using MLOps workflows (e.g., MLFlow, Kubeflow), including monitoring, orchestrating, and scaling production models
• Hands-on deployment experience across multiple environments and platforms
• Experience integrating machine learning and analytical tools
• Background working in strategic planning or consultant environments supporting government or DoD clients
• Proven track record of expanding technical scope or footprint with government customers
• Knowledge of the Army software development process and its technologies