Machine Learning Engineer - Training & Simulation Systems - 28036

HII's Mission Technologies division•Virginia Beach, VA

4d•$95,004 - $128,000•Onsite

About The Position

HII Mission Technologies is seeking a Machine Learning Engineer to support the design, development, and deployment of advanced training and simulation capabilities within the Advanced Training Domain (ATD) System—a shipboard combat system trainer that enhances U.S. Navy operational readiness. This full‑time, on‑site role is part of a high‑performing engineering team delivering mission‑driven solutions that improve warfighter training and decision‑making. In this role, you will help integrate machine‑learning and data‑driven capabilities that elevate the realism, adaptability, and performance of next‑generation combat system training environments. 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 solve operationally relevant challenges Grow your skills through hands‑on work with high‑fidelity simulation systems, real‑world training data, and modern ML/AI toolchains Contribute to innovations that shape future combat system training platforms

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 and 6 years of relevant experience
Experience developing and deploying machine learning 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/evaluation workflows
Ability to troubleshoot complex software, data, or model‑related issues
Ability to otain a DoD Information Assurance Technician (IAT) Level II certification or higher (e.g., 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

Nice To Haves

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 (e.g., 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

Responsibilities

Participate in Agile sprint planning and execution across cross‑functional engineering teams
Design, develop, and deploy machine learning models supporting 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
Develop supporting documentation such as architecture diagrams, data‑flow documentation, model cards, evaluation reports, and code commentary
Conduct developer testing in lab environments and aboard ship when required
Provide occasional on‑site support for installations, model validation, and user evaluations (up to 10% travel)
Perform additional related duties as assigned to support project and organizational needs