Machine Learning Engineer

Integer Technologies • Gulfport, MS

82d

About The Position

Integer Technologies is seeking a Machine Learning Engineer to develop, optimize, and deploy AI/ML methods that power perception and autonomy for maritime platforms. This role sits at the intersection of data science and software engineering: you will design models that turn raw maritime sensor data into reliable detection, classification, and situational awareness, and you will be responsible for integrating those models into production software that runs on the edge. Candidates must be U.S. citizens, eligible for a DoD security clearance, and capable of working across multidisciplinary teams to deliver scalable, maintainable, and mission-ready systems. Experience in maritime autonomy, sensor fusion, and distributed systems is highly desirable.

Requirements

• Must be a U.S. Citizen with the ability to obtain and maintain a U.S. DoD Secret Clearance.
• Bachelor’s degree in relevant fields (e.g., data science, computer science, computer engineering, electrical engineering, mechanical engineering, or other related field) and 7+ years of experience relevant to primary responsibilities outlined above.
• OR Master’s degree in relevant field (e.g., data science, computer science, computer engineering, electrical engineering, mechanical engineering, or other related field) and 5+ years of experience relevant to primary responsibilities outlined above.
• Strong proficiency in modern programming languages (e.g., C++, Python) and common ML frameworks (e.g., PyTorch or TensorFlow), with solid software engineering fundamentals and experience using Git.
• Demonstrated experience taking ML models from prototype to integrated software.
• Solid foundation in the mathematics underpinning ML, including linear algebra, probability and statistics, and signal processing.
• Experience working with real sensor data and an understanding of the challenges of noisy, real-world signals.
• Excellent written and oral communication skills, and the ability to collaborate effectively across disciplines.

Nice To Haves

• Ph.D. in relevant field (e.g., data science, computer science, computer engineering, electrical engineering, mechanical engineering, or other related field).
• Experience developing robotic or autonomous systems, using data from various perception sensor types (sonar, magnetic, cameras, lidar, etc.) to enhance a robotic platform's perception of its surrounding environmental and potential navigational hazards.
• Experience with unmanned and autonomous systems research involving maritime autonomous systems such as uncrewed surface vessels and uncrewed underwater vessels.
• Experience with edge processing.
• Understanding of the Navy and Department of Defense’s mission, problem set, and strategy for the integration of autonomous systems.

Responsibilities

• Design, train, and evaluate machine learning and deep learning models for detection, classification, segmentation, tracking, and signal analysis using maritime sensor data, with particular emphasis on sonar and other maritime sensors.
• Develop methods to process, fuse, and exploit heterogeneous sensor streams (sonar, magnetics, IMU, etc.) to produce robust perception in challenging maritime conditions.
• Optimize and deploy models for real-time inference on size, weight, and power constrained edge compute, applying techniques such as quantization, pruning, distillation, and hardware acceleration (e.g., GPU/CUDA, TensorRT, embedded accelerators).
• Integrate ML components into production software and autonomy pipelines, ensuring reliable interfaces with sensors, middleware, and downstream systems; write well-tested, maintainable code under version control.
• Build pipelines and tooling for data ingestion, labeling, augmentation, and the creation of training and validation datasets that reflect real operational environments.
• Stay current with advances in AI/ML and signal processing, and identify opportunities to extend perception and autonomy capabilities based on evolving mission requirements.
• Work across multidisciplinary teams and external partners, and contribute to a culture of technical excellence, knowledge sharing, and development best practices.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior