ML Ops Engineer - Clearance Required
Logistics Management Institute28 days ago
Remote, United States or Pittsburgh, PA, USAMid Level
Base Salary
$110k - $185k/yr
Responsibilities
- Build, train, validate, and evaluate machine learning models using tools such as Scikit-Learn and TensorFlow.
- Research, develop, and implement generative AI applications for complex real-world challenges.
- Deploy machine learning models to web-based applications and operational environments.
- Develop scalable MLOps pipelines for deploying generative AI systems across multiple environments.
- Design data manipulation and pipelining workflows using Pandas and PySpark.
- Support CI/CD pipelines for machine learning model development and deployment.
- Collaborate with engineering and DevSecOps teams on scalable cloud-based deployments.
- Work directly with Army stakeholders to identify ML integration opportunities and provide technical solutions.
- Translate operational needs and feedback into technical requirements and strategies with product leads.
- Mentor junior team members and lead discussions on architecture, system design, technology adoption, and team development.
- Maintain relationships with government customers and stakeholders through hybrid on-site engagement.
- Contribute to technical narratives, white papers, proposals, and strategic documentation.
Requirements
- Bachelor’s degree in Computer Science, Data Science, Software Engineering, or a related field.
- At least 3 years of experience in machine learning engineering, including MLOps, model development, and deployment.
- Expertise with data manipulation and pipelining technologies such as Pandas or PySpark.
- Hands-on experience with Scikit-Learn, MLlib, TensorFlow, PyTorch, or similar machine learning tools.
- Experience deploying AI/ML models in production web-based applications.
- Advanced Python proficiency and experience with Python web frameworks such as Flask, Django, or FastAPI.
- Hands-on understanding of containerization technologies such as Docker and Kubernetes.
- Familiarity with CI/CD practices, version control systems such as Git, and Agile or Scrum methodologies.
- Active Secret Clearance is required.
- Preferred qualifications include a master’s degree, 7+ years of directly related experience, MLOps workflow experience with tools such as MLFlow or Kubeflow, multi-environment deployment experience, government or DoD consulting experience, and knowledge of Army software development processes.
Benefits
- The position is available in the United States as remote or in Pittsburgh, Pennsylvania, with hybrid on-site engagement.
- The role requires approximately 10% travel.
Tech Stack
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