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, efficient applications while addressing operational needs for the United States Army. The ML Ops Engineer will work at the intersection of advanced AI/ML development, machine learning system deployment, and mission-critical applications, ensuring end-to-end lifecycle management of AI capabilities.

This position provides an exciting opportunity to collaborate directly with the Army to design cutting-edge generative AI tools and machine learning systems to empower their operations and decision-making. Candidates should thrive in a fast-paced, collaborative environment and demonstrate technical creativity, continuous learning, and problem-solving expertise.

Leveraging our mission-ready technology and solutions, proven expertise in federal deployment, and strategic relationships, we enhance outcomes for the government, efficiently and effectively. With a focus on agility and collaboration, LMI serves the defense, space, healthcare, and energy sectors—helping agencies navigate complexity and outpace change. Headquartered in Tysons, Virginia, LMI is committed to delivering impactful results that strengthen missions and drive lasting value.

Responsibilities:

• Build, train, validate, and evaluate machine learning models using technologies such asScikit-Learn,TensorFlow, or similar tools.
• Research, develop, and implementgenerative AI applications, ensuring that models address complex real-world challenges effectively.
• Deploy machine learning models toweb-based applicationsand integrate them into operational environments.
  • Operationalize generative AI systems by developing robust, scalable pipelines for deployment across multiple environments.
  • Design and implement advanceddata manipulation and pipeliningworkflows using tools such asPandasandPySparkto 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 LMI27s 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.

Percentage of Travel Required: 10%

Minimum Qualifications:

• Bachelor27s degree inComputer 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 indata manipulation & pipelining technologies, such asPandasorPySpark.
• Hands-on experience developing machine learning models using tools such asScikit-Learn,MLlib,TensorFlow,PyTorch, etc.
• Practical experience in deploying AI/ML models in productionweb-based applications.
• Advanced proficiency withPythonandPython-based web frameworks(e.g.,Flask,Django,FastAPI, etc.).
• Strong understanding and hands-on experience withcontainerization technologies, such asDockerandKubernetes.
• Familiarity withAgile or Scrum methodologies,CI/CD practices, andversion control systems(e.g., Git).
• Comfort operating in ambiguous and dynamic environments requiring proactive problem-solving.
• Active Secret Clearance required

Additional Preferred Qualifications:

• Master27s degree in Computer Science, Software Engineering, Information Systems, or related field.
• 7+ years of directly related experience.
• Proven track record usingMLOps 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.

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Target salary range: $110,075 - $185,138

Disclaimer: 

The salary range displayed represents the typical salary range for this position and is not a guarantee of compensation. Individual salaries are determined by various factors including, but not limited to location, internal equity, business considerations, client contract requirements, and candidate qualifications, such as education, experience, skills, and security clearances.