Multimodal AI System Engineer / DoD
A cutting-edge technology organization focused on transforming maritime domain awareness is looking for an AI Systems Engineer - Multi-Modal to join its highly collaborative engineering team. This role focuses on innovating machine learning and sensor fusion solutions that enable real-time insights from diverse data sources (e.g., vision, RF, acoustic) across distributed platforms. You'll help shape the future of real-world intelligence systems used to monitor remote environments and support critical decision-making.
This is a full-time opportunity with flexibility around remote work and offers a chance to contribute to mission-driven projects where initiative and deep technical expertise are highly valued. Required Skills & Experience
• 7+ years of professional experience building and deploying advanced machine learning systems, especially those involving multiple sensor modalities (vision, RF, acoustics).
• Master's or PhD in Machine Learning, Computer Vision, Signal Processing, Robotics, Computer Science, or a closely related discipline.
• Expertise with Python and deep learning frameworks such as PyTorch or TensorFlow.
• Strong knowledge of sensor fusion principles, data alignment, and feature extraction across heterogeneous data sources.
• Demonstrated ability to transition models from research prototypes to reliable, production-grade execution.
• Effective communicator who can partner with engineering, product, and domain experts across disciplines.
Desired Skills & Experience
• Prior work on embedded or edge-focused systems with real-time performance constraints.
• Familiarity with maritime, aerospace, robotics, or other sensor-rich deployment environments.
• Comfortable navigating ambiguity and driving model design from first principles through validation and optimization.
• Experience with best practices in code quality, experiment tracking, and reproducible workflows.
What You Will Be Doing Tech Breakdown:
• 55% Design, develop, and validate multi-modal machine learning components
• 45% Pipeline architecture, optimization, and cross-disciplinary collaboration
Daily Responsibilities:
• Partner with system engineers and domain specialists to translate raw sensor streams into robust model inputs.
• Architect and implement multi-modal data pipelines including alignment, augmentation, and preprocessing.
• Prototype and scale new machine learning approaches that combine diverse inputs (e.g., video, radio frequency, acoustics).
• Optimize models and inference workflows for deployment on resource-constrained and remote-connected systems.
• Document design decisions, training strategies, and evaluation results to support repeatability and cross-team understanding.
The Offer You will receive the following benefits:
• Competitive base salary with budget for education and professional development.
• Flexible schedule with remote-first collaboration.
• Opportunity to make a tangible impact advancing real-world perception systems.
• Work alongside a passionate, mission-oriented team that values innovation and autonomy
#LI-OP
Apply Now
Apply Now
This is a full-time opportunity with flexibility around remote work and offers a chance to contribute to mission-driven projects where initiative and deep technical expertise are highly valued. Required Skills & Experience
• 7+ years of professional experience building and deploying advanced machine learning systems, especially those involving multiple sensor modalities (vision, RF, acoustics).
• Master's or PhD in Machine Learning, Computer Vision, Signal Processing, Robotics, Computer Science, or a closely related discipline.
• Expertise with Python and deep learning frameworks such as PyTorch or TensorFlow.
• Strong knowledge of sensor fusion principles, data alignment, and feature extraction across heterogeneous data sources.
• Demonstrated ability to transition models from research prototypes to reliable, production-grade execution.
• Effective communicator who can partner with engineering, product, and domain experts across disciplines.
Desired Skills & Experience
• Prior work on embedded or edge-focused systems with real-time performance constraints.
• Familiarity with maritime, aerospace, robotics, or other sensor-rich deployment environments.
• Comfortable navigating ambiguity and driving model design from first principles through validation and optimization.
• Experience with best practices in code quality, experiment tracking, and reproducible workflows.
What You Will Be Doing Tech Breakdown:
• 55% Design, develop, and validate multi-modal machine learning components
• 45% Pipeline architecture, optimization, and cross-disciplinary collaboration
Daily Responsibilities:
• Partner with system engineers and domain specialists to translate raw sensor streams into robust model inputs.
• Architect and implement multi-modal data pipelines including alignment, augmentation, and preprocessing.
• Prototype and scale new machine learning approaches that combine diverse inputs (e.g., video, radio frequency, acoustics).
• Optimize models and inference workflows for deployment on resource-constrained and remote-connected systems.
• Document design decisions, training strategies, and evaluation results to support repeatability and cross-team understanding.
The Offer You will receive the following benefits:
• Competitive base salary with budget for education and professional development.
• Flexible schedule with remote-first collaboration.
• Opportunity to make a tangible impact advancing real-world perception systems.
• Work alongside a passionate, mission-oriented team that values innovation and autonomy
#LI-OP
Apply Now
Apply Now