We are an IT and Engineering staffing agency in search of a Deep Learning Engineer for our client. Our client is a leading U.S.-based defense technology firm specializing in the design and deployment of Autonomous Underwater Vehicles (AUVs) that support national security, deep-sea research, and commercial maritime operations. These highly advanced systems combine precision engineering, AI-based autonomy, and rugged reliability to operate in extreme underwater environments.
The company is at the forefront of innovation in autonomy, perception, and sensor fusion, and is seeking a Senior Deep Learning Engineer to help develop mission-critical onboard intelligence and situational awareness capabilities. This role will have a direct impact on next-generation defense and surveillance solutions by integrating neural network models that enable real-time environmental understanding and decision-making in autonomous maritime systems.
Typical Duties and Responsibilities
- Design, train, test, and deploy deep learning models for object detection, scene segmentation, target recognition, and anomaly detection in underwater environments.
- Collaborate with robotics engineers, control systems teams, and sonar/image processing experts to fuse data from multimodal sensors (e.g., sonar, LIDAR, optical cameras, acoustic arrays).
- Develop and optimize neural networks using frameworks such as PyTorch, TensorFlow, or ONNX for real-time inference on embedded computing platforms.
- Implement transfer learning and model compression techniques to optimize models for edge deployment (e.g., NVIDIA Jetson, Intel Movidius, or custom FPGA/GPU hardware).
- Integrate deep learning models into autonomy frameworks using ROS, DDS, or custom control architectures.
- Validate model performance using real-world sea trial datasets, synthetic simulation environments, and laboratory testbeds.
- Support data preprocessing, augmentation, and labeling pipelines with tools like OpenCV, Labelbox, or CVAT.
- Collaborate with government agencies, naval research labs, and classified partners on AI-enabled mission systems.
- Ensure compliance with DoD AI ethics, ITAR regulations, and cybersecurity protocols under NIST 800-171 and CMMC 2.0
Education
- Master’s Degree in Computer Science, Artificial Intelligence, Machine Learning, Robotics, or a related STEM field is required.
- Ph.D. strongly preferred, especially with published research in computer vision, neural networks, or autonomous systems.
Required Skills and Experience
- 7+ years of experience developing and deploying deep learning solutions in real-time, embedded, or robotics applications.
- Proficiency in Python, C++, and at least one deep learning framework (e.g., PyTorch, TensorFlow, Keras).
- Strong understanding of convolutional neural networks (CNNs), recurrent networks (RNNs/LSTMs), and transformer architectures.
- Experience working with SLAM, sensor fusion, or 3D computer vision in autonomous vehicles or robotics.
- Hands-on experience with GPU acceleration, CUDA programming, or inference optimization for edge computing.
- Familiarity with version control (Git), CI/CD pipelines, and containerization tools like Docker.
- Strong mathematical foundation in linear algebra, probability, and optimization.
- U.S. Citizenship required due to work on ITAR-restricted projects
Preferred Qualifications
- Prior experience in maritime robotics, autonomous underwater vehicles, or unmanned systems (AUVs/UUVs/ROVs).
- Familiarity with acoustic data processing, underwater SLAM, and sonar image classification.
- Experience working in a DoD, DARPA, or Navy SBIR/STTR-funded environment.
- Exposure to synthetic data generation, physics-informed ML, or sim-to-real transfer learning.
- Publications or patents in the field of robotic perception, AI for autonomy, or underwater sensing.
- Active or prior DoD security clearance is a plus.
