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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

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