Responsibilities Peraton is seeking a talented Software Engineer to support the integration of machine learning models into an advanced ground research and development environment. This role involves collaborating with external stakeholders to deploy, optimize, and maintain machine learning solutions within a high-performance computing infrastructure. The ideal candidate will have experience with software development, model deployment, and performance tuning, along with a strong understanding of machine learning frameworks and algorithms. This is a unique opportunity to contribute to cutting-edge research and drive innovation in a dynamic and fast-paced research and development (R&D) environment. What you'll do: Provide TS/SCI machine learning model integration into R&D environments Install, configure, and maintain Linux servers while ensuring system performance, security, and stability. Design, implement, and manage containerized applications using AWS Cloud Containerization services (e.g., ECS, EKS) and Docker, developing CI/CD pipelines for automated deployment and scaling. Work closely with cross-functional teams to understand project requirements and deliver robust solutions, documenting system configurations, procedures, and best practices. Qualifications Required Qualifications: Associates degree and seven (7+) years of relevant experience; OR Bachelors degree with five (5+) years of relevant experience; OR Masters degree with three (3+) years of relevant experience. Four (4) additional years of experience will be considered in lieu of Bachelors degree. This position requires an active TS/SCI with poly. The candidate must maintain the clearance. Active CompTIA Security+ certification Experience developing software on Unix-based operating systems such as RedHat Enterprise Linux and using AWS as a developer. Expertise implementing machine learning models into cloud native environment and utilizing containerization platforms such as AWS Cloud Containerization services, Docker, and others. Strong proficiency in containerization technologies, including AWS Cloud Containerization services and Docker. Experience with CI/CD tools and practices. Solid understanding of networking, security, and system architecture. Desired Qualifications: Experience in the Intelligence Community with systems engineering focus. Experience integrating machine learning into AWS environments. Familiarity integrating machine learning models that improve compute resource management, data transfer latency, low-to-high data transfers and API management. Familiarity with Kubernetes and other container orchestration platforms. Experience with infrastructure as code tools (e.g., Terraform, CloudFormation). Knowledge of scripting languages (e.g., Python, Bash). Familiarity with Palantir products (Foundry, Apollo). Benefits: Peraton offers enhanced benefits to employees working on this critical National Security program, which include heavily subsidized employee benefits coverage for you and your dependents, 25 days of PTO accrued annually up to a generous PTO cap and eligible to participate in an attractive bonus plan. Peraton Overview Peraton is a next-generation national security company that drives missions of consequence spanning the globe and extending to the farthest reaches of the galaxy. As the world's leading mission capability integrator and transformative enterprise IT provider, we deliver trusted, highly differentiated solutions and technologies to protect our nation and allies. Peraton operates at the critical nexus between traditional and nontraditional threats across all domains: land, sea, space, air, and cyberspace. The company serves as a valued partner to essential government agencies and supports every branch of the U.S. armed forces. Each day, our employees do the can't be done by solving the most daunting challenges facing our customers. Visit peraton.com to learn how we're keeping people around the world safe and secure. Target Salary Range $104,000 - $166,000. This represents the typical salary range for this position based on experience and other factors. All