Machine Learning Engineer - Training & Simulation Systems (Engineer Machine Learning 2)
Job Description
HII Mission Technologies is seeking a full-time, on-site Machine Learning Engineer to build training and simulation capabilities for the Advanced Training Domain (ATD) System supporting U.S. Navy operational readiness.
Responsibilities
- Participate in Agile sprint planning and execution with cross-functional engineering teams
- Design, develop, and deploy machine learning 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, including performance tuning, error analysis, and model explainability
- Produce supporting documentation including architecture diagrams, data-flow documentation, model cards, evaluation reports, and code commentary
- Perform developer testing in lab environments and aboard ship when required
- Provide occasional on-site support for installations, model validation, and user evaluations (travel up to 10%)
- Complete additional related duties as assigned to support project and organizational needs
Requirements
- 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 plus 6 years of relevant experience
- Experience developing and deploying ML models with Python frameworks such as PyTorch, TensorFlow, or Scikit-learn
- Hands-on 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 issues across software, data, and model components
- Obtain a DoD Information Assurance Technician (IAT) Level II certification or higher (example: Security+ CE, CCNA Security, CySA+) within 3 months of hire if not currently held
- U.S. Citizen
- Must hold an active or current DoD Secret clearance
Technologies
- Python, PyTorch, TensorFlow, Scikit-learn
- Linux
- Agile, Scrum
- Security+ CE, CCNA Security, CySA+
- Containers, APIs, embedded inference engines
Benefits
- Best-in-class medical, dental, and vision plan choices
- Wellness resources
- Employee Assistance Programs
- Savings Plan Options (401(k))
- Financial planning tools
- Life insurance
- Employee discounts
- Paid holidays and paid time off
- Tuition reimbursement
- Early childhood and post-secondary education scholarships
Impact, Growth & Development
- Strengthen U.S. Navy readiness by engineering ML solutions that improve training fidelity and system performance
- Collaborate with software engineers, data engineers, analysts, and end users to address operational challenges
- Build skills through hands-on work with high-fidelity simulation systems, real-world training data, and modern ML/AI toolchains
- Contribute to innovations shaping future combat system training platforms
Preferred Requirements
- Degree in Computer Science, Data Science, ML/AI, Engineering, or a related technical field
- IAT Level II certification or higher (example: 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 (example: 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
Physical Qualifications
- May require working in an office, industrial, shipboard, or laboratory environment
- Must be capable of climbing ladders and tolerating confined spaces and a range of temperature conditions during shipboard or testing activities
Required Travel
- 0 - 10%
Role Details
- Location: Virginia Beach, VA (on-site)
- Employment type: Full Time / Salaried / Exempt
- Level: Mid
- Anticipated salary range: $95,004 - $122,000 per year
- Security clearance: Secret
- Technology focus: Training and simulation systems using ML and data-driven capabilities for the ATD System