Artificial Intelligence Developer – RangeOS at Motorambar Inc

Hanover, Maryland, United States -

Full Time

Start Date

Immediate

Expiry Date

28 Jan, 26

Salary

0.0

Posted On

30 Oct, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Artificial Intelligence, Machine Learning, Cybersecurity, Natural Language Processing, Reinforcement Learning, Anomaly Detection, Python, TensorFlow, PyTorch, Docker, Kubernetes, Agile, DevSecOps, Data Science, CI/CD, Linux

Industry

IT Services and IT Consulting

Description

Responsibilities Design, develop, and deploy AI/ML models to support cyber training, threat emulation, and decision support. Integrate AI capabilities into microservices in the cloud and on-premises and distributed simulation environments. Develop and maintain data pipelines, model training workflows, and inference services. Collaborate with DevSecOps teams to integrate AI components into CI/CD pipelines. Apply natural language processing (NLP), reinforcement learning, or anomaly detection techniques to enhance cyber range realism. Optimize model performance and scalability across Linux-based systems and containerized environments. Support the development of intelligent agents and behavior models for simulated adversaries and network traffic. Maintain detailed documentation of AI models, training datasets, and evaluation metrics. Participate in Agile development cycles, sprint planning, and technical reviews. Ensure AI solutions meet DoD security, performance, and interoperability standards. Qualifications Bachelor’s degree in Computer Science, Artificial Intelligence, Data Science, or related field. IAT Level II certification in accordance with DoDD 8570. Active Secret clearance required; TS/SCI strongly preferred. Minimum of 5+ years of experience in AI/ML development, software engineering, or data science. Proficiency in Python and AI/ML frameworks such as TensorFlow, PyTorch, or Scikit-learn. Experience with containerization (Docker) and orchestration platforms (Kubernetes, OpenShift). Familiarity with CI/CD tools such as Jenkins, GitLab CI, or similar. Strong understanding of Linux-based systems, virtualization (VMware, KVM), and cloud-native architectures. Experience developing and deploying AI models in classified or isolated environments. Working knowledge of Agile and DevSecOps methodologies. Preferred Qualifications Experience supporting PCTE, RangeOS, or other DoD cyber range programs. Background in Cybersecurity, Modeling & Simulation, or Distributed Interactive Simulation (DIS). Familiarity with REST APIs, automated testing frameworks, and data labeling tools. Experience with synthetic data generation, adversarial AI, or cyber threat intelligence modeling. CompTIA Security+, CEH, or other relevant certifications. Familiarity with DoD software accreditation, RMF, and secure deployment practices Special Requirements/Security Clearance Active DOD SECRET Clearance required Strong analytical and problem-solving skills. Excellent communication skills, both written and verbal. Ability to make critical decisions with domain expertise that impact overall project implementation. Leadership skills with the ability to supervise and guide teams. Ability to work in a fast-paced, client-focused environment, managing multiple priorities effectively. This is a full-time role with an opportunity to lead and contribute to cutting-edge cloud security and AI-driven security initiatives. Strong analytical and problem-solving skills with the ability to operate independently in fast-paced technical teams. Mission-focused, detail-oriented, and capable of working across development, AI, and cyber operations disciplines. Excellent communication and collaboration skills for interfacing with government customers, software developers, and range operators. Commitment to continuous learning and innovation in AI/ML technologies within a secure, Agile development environment.

Responsibilities

The role involves designing, developing, and deploying AI/ML models for cyber training and threat emulation. Additionally, the developer will integrate AI capabilities into microservices and collaborate with DevSecOps teams.