About the position

PMAT is seeking a Senior Machine Learning Engineer to design, develop, and implement advanced machine learning models and algorithms in support of naval applications. This role requires deep technical expertise in modern machine learning methods, distributed systems, cloud-native development, and software engineering best practices. The Senior ML Engineer will collaborate with multidisciplinary teams to deliver mission-focused AI solutions that integrate into operational Navy environments.

Responsibilities

• Design, develop, and implement machine learning models and algorithms for naval applications.
• Develop and deploy algorithms, mathematical models, and machine learning models into real-world operational environments.
• Perform data preprocessing, feature engineering, model evaluation, and validation.
• Collaborate with engineers, data scientists, and mission stakeholders to align ML solutions with operational requirements.
• Develop cloud-native ML pipelines using AWS, Azure, Docker, Kubernetes, or equivalent platforms.
• Implement ML solutions using frameworks such as TensorFlow, PyTorch, and scikit-learn.
• Contribute to distributed computing and parallel processing approaches to optimize ML model performance.
• Participate in CI/CD pipeline development, automation, and DevSecOps workflows.
• Apply cybersecurity principles in the design and deployment of machine learning systems.
• Provide documentation, technical reports, and engineering artifacts consistent with PMAT and government standards.
• Stay current with advancements in machine learning, data science, and emerging technologies relevant to naval and DoD applications.

Requirements

• Experience as a data scientist, data engineer, geospatial engineer, machine learning engineer, or software engineer.
• Proven experience developing and deploying algorithms, mathematical models, or machine learning models in real-world applications.
• Strong programming skills in Python.
• Familiarity with cloud platforms (e.g., AWS, Azure) or containerization technologies (e.g., Docker, Kubernetes).
• Familiarity with software engineering best practices, including Git.
• Strong programming skills in Java, C++, Go, or Rust.
• Strong analytical, problem-solving, and communication skills.
• Ability to work effectively in a collaborative team environment.
• Ability to safely carry tools, equipment, and materials aboard ship, including ascending and descending shipboard ladders(stairwells) and navigating confined spaces while maintaining required points of contact. Tools and equipment will weigh no more than 50 lbs.
• Ability to perform required work aboard Navy vessels and in shipboard environments, including navigating narrow passageways, ascending and descending ladders (stairwells), working on elevated platforms, and operating in variable sea conditions.
• Ability to perform activities on a recurring basis during shipboard operations or testing evolutions.
• Ability to comply with Navy safety requirements and wear required personal protective equipment (PPE).
• Candidates should be prepared to complete a coding exercise as part of the interview process.
• US Citizenship
• No dual citizenship
• Active DoD TS clearance required

Nice-to-haves

• Experience with distributed computing and parallel processing.
• Experience with CI/CD pipelines and automation tools (GitHub Actions, GitLab CI, Jenkins).
• Experience with ML frameworks such as TensorFlow, PyTorch, or scikit-learn.
• Experience with cloud-native architecture and software API design.
• Experience integrating machine learning into operational DoD systems or edge computing environments.
• Familiarity with DoD AI strategies, MLOps, or data engineering in secure environments.
• Previous experience supporting government agencies or military organizations. (NAVWAR, NIWC Pacific, or other Navy C2/ISR programs strongly preferred).
• Active DOD TS SCI preferred
• Bachelor of Science in Computer Science, Data Science, Geography, Math, Machine Learning, or Statistics, OR Equivalent years of relevant experience in lieu of a degree
• Additional certifications in cloud, data engineering, GIS, or cybersecurity are a plus