Jobs at nou Systems, Inc.

Build and maintain GPU-capable development environments, containerized workflows, and GitLab CI/CD pipelines for machine learning teams. Develop shell scripts, enforce code quality and merge request standards, standardize ML development practices, and support secure deployments in DoD-restricted environments. Collaborate with researchers, software engineers, and cybersecurity teams to transition prototypes into production. Contribute to SBIR/STTR project execution, technical documentation, onboarding, and proposal development.

Develop, train, and deploy AI/ML systems, including deep reinforcement learning, explainability, adversarial learning, and interpretability solutions. Architect AI systems, design training datasets, implement research-based models, develop MLOps pipelines, and communicate results to technical and nontechnical audiences. Lead multidisciplinary projects, support proposals and conferences, mentor junior engineers, and collaborate across teams. The role requires strong Python development, deep learning expertise, research literacy, customer interaction, and an active or obtainable Secret clearance.

Build and maintain GPU-capable development environments, containerized workflows, and GitLab CI/CD pipelines for machine learning teams. Develop automation, enforce code quality and merge-request standards, document standardized ML practices, and support secure deployment in DoD-restricted environments. Collaborate with researchers, software engineers, and cybersecurity teams to transition prototypes into production-ready systems while contributing to SBIR/STTR projects and proposals.

Leads front-end systems engineering for large-scale DoD IT modernization initiatives. Responsibilities include requirements development, current-state baselining, target architecture definition, alternatives analysis, data center consolidation, workload migration planning, requirements traceability, technical documentation, and stakeholder coordination across infrastructure, applications, cybersecurity, and program management teams.

Designs, develops, and executes system-level tests for ground-based radar hardware and software. Creates test plans, procedures, scripts, specifications, and reports; analyzes test data; identifies defects; troubleshoots updates; and supports modernization, integration, and formal government testing. Collaborates with systems engineering, software, hardware, cybersecurity, and logistics teams while ensuring testing meets requirements, standards, schedules, and operational expectations.

Develop, train, analyze, and customize supervised and reinforcement learning models; design training datasets; build MLOps pipelines; and communicate results to technical and nontechnical teams. The role requires Python and deep learning experience with PyTorch, TensorFlow, or JAX, plus eligibility for an active Secret clearance. Preferred experience includes RL frameworks, MLOps and DevOps tools, time series, satellite imagery, graph neural networks, and advanced RL algorithms.

Designs, develops, documents, tests, debugs, and maintains software supporting ground-based radar modernization and sustainment. Collaborates with systems, hardware, and software engineering teams to develop applications, web and desktop software, autonomous services, scripts, and utilities. Analyzes user and mission needs, resolves system capability issues, supports technical planning, and ensures software standards, performance, cost, and schedule objectives are met.

Designs, develops, integrates, tests, maintains, and sustains hardware for ground-based missile-warning and space-surveillance radars. Responsibilities include hardware configuration analysis, reliability and obsolescence management, technical documentation, system integration, troubleshooting, testing, and maintenance planning. The role supports Space Force strategic warning and surveillance systems and requires a STEM bachelor’s degree, relevant hardware or radar experience, U.S. citizenship, and an active or obtainable Secret clearance.

Designs, develops, and executes system-level tests for ground-based radar hardware and software. Creates test plans, procedures, scripts, specifications, and reports; analyzes results; troubleshoots issues; documents defects; and verifies requirements. Coordinates personnel, schedules, equipment, and formal government testing while collaborating with systems engineering, software, hardware, cybersecurity, and logistics teams to support radar modernization and sustainment.

Systems Engineer supporting Ground Based Radar maintenance, sustainment, modernization, and integration. Responsibilities include requirements engineering, functional and trade studies, system architecture, interface definition, validation and verification, systems integration, operational performance analysis, lifecycle cost analysis, and technical modernization planning. The role collaborates across hardware, software, and systems engineering teams while supporting missile defense radar capabilities and requires an active Secret clearance or eligibility to obtain one.

Develop, train, evaluate, and deploy machine learning models using Python and PyTorch for defense applications. Build backend software, data pipelines, APIs, and system integrations supporting ML workflows. Prepare datasets, implement published ML methods, work in Linux-based containerized environments, and collaborate across project teams. Document and communicate technical results while contributing to development processes and operationally relevant prototypes.