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
