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Design and operate Kubernetes-based platforms for AI/ML systems, manage containerized environments, and develop CI/CD pipelines for secure deployment in mission-critical settings.

The R&D Engineer will build and refine software solutions for defense use cases, prototype systems, and convert stakeholder feedback into technical requirements. Collaboration with engineering teams and customer-oriented engagements are key responsibilities.

Lead the capture lifecycle in the DoD sector, developing strategies, proposals, and alliances. Build relationships with decision-makers and represent the company at events.

Lead the design and development of mission-relevant software, build backend services and APIs, mentor engineers, and support technical demos.

As a Computer Science Intern, you will assist in software development, conduct research, troubleshoot issues, and collaborate with teams on projects.

The role involves supporting a US Air Force program by building and maintaining a DevSecOps platform, focusing on Kubernetes clusters, Terraform, and Helm charts, while ensuring compliance with cybersecurity policies.

The MLOps Engineer will manage the ML system lifecycle, deploy models in mission-critical environments, and ensure reliability through monitoring and infrastructure optimization. They will work with cloud-native technologies and focus on operationalizing AI/ML capabilities within classified settings.

The AI/ML Engineer will design and deploy machine learning solutions, build model architectures, collaborate with teams, and ensure model performance and scalability.