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