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

HII Mission Technologies is seeking a full-time, on-site Machine Learning Engineer to design, develop, and deploy training and simulation capabilities for the Advanced Training Domain (ATD) System that supports U.S. Navy operational readiness. The role applies machine learning and data-driven methods to increase training realism, adaptability, and performance.

Role Responsibilities

• Participate in Agile sprint planning and execution across cross-functional engineering teams
• Design, develop, and deploy machine learning models to support 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 materials such as 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, with travel of up to 10%
• Complete additional related duties as assigned to support project and organizational needs

Required 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
• Experience developing and deploying ML models using 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 and evaluation workflows
• Ability to troubleshoot complex issues related to software, data, or models
• Ability to obtain DoD Information Assurance Technician (IAT) Level II certification or higher (examples: Security+ CE, CCNA Security, CySA+) within 3 months of hire if not currently held
• Must be a U.S. Citizen
• Must hold a current or active DoD Secret clearance

Preferred Qualifications

• Degree in Computer Science, Data Science, ML/AI, Engineering, or related technical field
• IAT Level II certification or higher (e.g., 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 (for 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

Technologies and Tools

• Python, PyTorch, TensorFlow, Scikit-learn
• Linux
• Agile, Scrum
• Security+ CE, CCNA Security, CySA+
• Containers, APIs, embedded inference engines

Impact, Growth & Development

• Support U.S. Navy readiness by engineering ML solutions that improve training fidelity and system performance
• Work with software engineers, data engineers, analysts, and end users to address operationally relevant challenges
• Build skills through hands-on experience with high-fidelity simulation systems, real-world training data, and modern ML/AI toolchains
• Contribute to innovations shaping future combat system training platforms

Compensation and Employment Details

• Location: Virginia Beach, VA (onsite)
• Employment type: Full Time, Salaried, Exempt
• Level: Mid
• Salary range: $95,004 - $122,000 per year
• Travel: 0 - 10%

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

Physical Qualifications

• May require work 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