Multimodal AI System Engineer / DoD

Remote in Remote, VA, US • Posted 30+ days ago • Updated 10 hours ago
Full Time
On-site
$180000 - $220000/yr
Fitment

Dice Job Match Score™

👾 Reticulating splines...

Job Details

Skills

  • DoD
  • Artificial Intelligence
  • Decision-making
  • Computer Vision
  • Signal Processing
  • Computer Science
  • Python
  • Deep Learning
  • PyTorch
  • TensorFlow
  • Fusion
  • Extraction
  • Research
  • Prototyping
  • Embedded Systems
  • Real-time
  • Aerospace
  • Robotics
  • Optimization
  • Sensors
  • Streaming
  • Machine Learning (ML)
  • Video
  • RF
  • Acoustics
  • Workflow
  • Information Design
  • Training
  • Evaluation
  • Budget
  • Professional Development
  • Collaboration
  • Innovation

Summary

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
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
  • Dice Id: 10105282
  • Position Id: 861132
  • Posted 30+ days ago
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