Machine Learning Engineer - Training & Simulation Systems (Engineer Machine Learning 2)

HII Mission Technologies is building advanced training and simulation capabilities for the Advanced Training Domain (ATD) System that supports U.S. Navy operational readiness . As a Machine Learning Engineer (Training & Simulation Systems), you will design and deploy machine learning solutions that improve training realism, adaptability, and performance, working in an on-site environment in Virginia Beach, VA . You will collaborate with cross-functional teams to bring ML and data-driven methods into Linux-based training systems. The work spans the full lifecycle, from collecting and preparing Navy training data to integrating trained models into operational environments. What you’ll do Participate in Agile sprint planning and execution with cross-functional engineering teams Design, develop, and deploy ML models for simulation accuracy , data analytics, performance prediction, and system-behavior modeling Build data pipelines for collection, preprocessing, labeling, and training using structured and unstructured Navy training data Integrate ML models into Linux-based training systems using containers , APIs , or embedded inference engines Troubleshoot, optimize, and maintain ML workflows through performance tuning, error analysis, and model explainability Create supporting deliverables including architecture diagrams , data-flow documentation, model cards , evaluation reports, and code commentary Perform developer testing in lab environments and, when required, aboard ship Provide occasional on-site support for installations, model validation, and user evaluations (up to 10% travel) Support additional project and organizational needs as assigned Qualifications 2 years of relevant experience with a Bachelor’s degree in a related field, or 0 years of experience with a Master’s degree in a related field, or High school diploma or equivalent and 6 years of relevant experience Hands-on experience building and deploying ML models with Python frameworks such as PyTorch , TensorFlow , or Scikit-learn Experience with Linux-based development environments Familiarity with Agile/Scrum methodologies Experience implementing data pipelines , feature engineering, and model training/evaluation workflows Ability to troubleshoot complex software, data, or model-related issues Ability to obtain a DoD Information Assurance Technician (IAT) Level II certification or higher (for example, Security+ CE , CCNA Security , CySA+ ) within 3 months of hire if not currently held Must be a U.S. Citizen Must hold a current/active DoD Secret clearance Technologies you’ll work with Python, PyTorch, TensorFlow, Scikit-learn, Linux, Agile, Scrum, Security+ CE, CCNA Security, CySA+, containers, APIs, embedded inference engines Impact, growth, and how your work matters Strengthen U.S. Navy readiness by engineering ML solutions that improve training fidelity and system performance Work alongside software engineers, data engineers, analysts, and end users to solve operationally relevant challenges Build skills through hands-on development with high-fidelity simulation systems, real-world training data, and modern ML/AI toolchains Contribute to innovations shaping future combat system training platforms Benefits Best-in-class medical, dental, and vision plan choices Wellness resources and employee assistance programs 401(k) Savings Plan options Financial planning tools Life insurance and employee discounts Paid holidays and paid time off Tuition reimbursement Early childhood and post-secondary education scholarships Additional details Employment type: Full Time / Salaried / Exempt Location: Virginia Beach, VA (onsite) Travel: 0 - 10% Clearance: Secret Salary range: $95,004 - $122,000 per year Level: Mid Physical qualifications: May require work in office, industrial, shipboard, or laboratory environments. Must be capable of climbing ladders and tolerating confined spaces and temperature variations during shipboard or testing activities. Preferred qualifications Degree in Computer Science, Data Science, ML/AI, Engineering, or related technical field IAT Level II certification or higher (Security+ CE, CCNA Security, CySA+) Experience with high-fidelity training systems, simulation environments, or Navy combat systems Experience deploying ML models in operational or real-time systems (REST APIs, message queues, embedded inference) Familiarity with ActiveMQ, messaging systems, or streaming-data frameworks Experience with MLOps tools such as GitLab CI/CD, Docker, Podman, Kubernetes, or virtualization technologies Background in data analysis for mission systems, sensor data, or tactical environments Experience with Jira, Git, or Subversion #J-18808-Ljbffr HII