> Markdown version of [/jobs/ext/1861062-machine-learning-engineer-training-simulation-systems-engin](https://www.wearedevelopers.com/jobs/ext/1861062-machine-learning-engineer-training-simulation-systems-engin). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Machine Learning Engineer - Training & Simulation Systems (Engin - **Company:** HII Mission Technologies - **Location:** Virginia Beach, VA, United States - **Experience:** Experienced - **Salary:** $95,004.0 - $128,000.0 - **Contract:** Permanent contract - **Skills:** Training Data, Apache ActiveMQ, Application Programming Interfaces (APIs), Agile Methodology, Artificial Intelligence, Data Analysis, JIRA, Cyber Security, Data Transformation, Linux, Data Flow Control, Machine Learning, Enterprise Messaging Systems, Performance Tuning, Scrum Methodology, Queueing Systems, Tensorflow, Data Streaming, Subversion, Virtualization Technology, Web Application Frameworks, Real Time Systems, Feature Engineering, Pytorch, Model Validation, Git, Gitlab-ci, Scikit Learn, Kubernetes, Information Technology, Data Analytics, Integration Frameworks, Machine Learning Operations, Restful APIs, Data Pipelines, Docker - **Published:** July 27, 2026 - **Apply:** https://www.clearancejobs.com/jobs/9059866/machine-learning-engineer-training-simulation-systems-engin ## About the Role * 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 * 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 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. ## Description * 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 ## Related Videos - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [Collaboration Quantified: Lessons from Open Source Developer Networks](https://www.wearedevelopers.com/videos/1422-collaboration-quantified-lessons-from-open-source-developer-networks) - [Docker network without Docker](https://www.wearedevelopers.com/videos/1418-docker-network-without-docker) - [DevOps for Machine Learning](https://www.wearedevelopers.com/videos/179-devops-for-machine-learning) - [Git for Code Reviews](https://www.wearedevelopers.com/videos/429-git-for-code-reviews) - [Effective Machine Learning - Managing Complexity with MLOps](https://www.wearedevelopers.com/videos/185-effective-machine-learning-managing-complexity-with-mlops) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [MLops – Deploying, Maintaining And Evolving Machine Learning Models in Production](https://www.wearedevelopers.com/magazine/115-mlops-deploying-maintaining-and-evolving-machine-learning-models-in-production) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [Why Upskilling And Reskilling is Important For Developers](https://www.wearedevelopers.com/magazine/428-why-upskilling-and-reskilling-is-important-for-developers)