ML Ops Engineer, Clearance Required

LMI

ML Ops Engineer supporting AI/ML development for the United States Army. Collaborating on operationalizing machine learning workflows and building generative AI tools.

Posted 4/29/2026full-timeRemote • Pennsylvania • 🇺🇸 United StatesMid-LevelSenior💰 $110,075 - $185,138 per yearWebsite

Tech Stack

Tools & technologies

CloudDjangoDockerFlaskKubernetesPandasPySparkPythonPyTorchScikit-LearnTensorflow

About the role

Key responsibilities & impact

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

What you’ll need

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

Benefits

Comp & perks

Health insurance
401(k) matching
Flexible work hours
Paid time off
Professional development opportunities

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

machine learningMLOpsmodel developmentmodel deploymentdata manipulationpipeliningPythoncontainerizationweb frameworksCI/CD

Soft Skills

problem-solvingmentoringcollaborationcommunicationleadership

Certifications

Bachelor’s degreeActive Secret Clearance