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Senior RF Machine Learning EngineerQuartermaster • Arlington, Texas, United States
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Senior RF Machine Learning Engineer

Quartermaster
  • US
    Arlington, Texas, United States
  • US
    Arlington, Texas, United States
Postuler Maintenant

À propos

We are looking for an Artificial Intelligence Engineer with an emphasis in Multi-Modal system to design, develop, and deploy machine learning systems that utilize diverse sensor data for real-time maritime intelligence. You’ll work at the intersection of vision, RF, acoustic, and natural language signals—building models that fuse these modalities to provide a robust and contextual understanding of vessel activity. This role is ideal for someone who thrives on ambiguity, bridges theory and implementation, and is excited by the challenge of building AI systems that work in dynamic, constrained, and remote environments.
Key Responsibilities:
Research, design, and implement advanced machine learning models that combine vision, RF, and acoustic signals for detection, classification, and tracking tasks
Architect sensor fusion pipelines that support robust, redundant, and context-aware perception in dynamic environments
Collaborate closely with domain experts and systems engineers to translate raw sensor data into actionable model inputs
Design and oversee data pipelines for multi-modal learning, including data alignment, augmentation, and pre-processing across modalities
Optimize models and inference workflows for low-latency execution on embedded and edge compute platforms
Lead performance analysis across individual and fused modalities, and drive strategies for improving robustness and generalization
Prototype and operationalize novel research in sensor fusion, uncertainty modeling, and representation learning
Contribute to long-term architectural decisions around multi-modal AI infrastructure, tooling, and evaluation frameworks
Document model design, training methodology, and validation processes with rigor and clarity
Qualifications (Preferred):
PhD or Master’s degree in Machine Learning, Computer Vision, Signal Processing, or a closely related field
7+ years of experience building and deploying machine learning systems, with a focus on multi-modal or sensor fusion applications
Proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow
Demonstrated experience working with camera imagery, RF signals and/or acoustic data
Deep understanding of signal alignment, temporal/spatial synchronization, and feature extraction across diverse data types
Proven ability to bridge research and application—delivering high-performance models in production contexts
Excellent communication and collaboration skills in cross-functional, interdisciplinary teams
Experience in maritime, aerospace, or other sensor-rich environments is a significant plus
Work Environment:
This is a remote position with collaboration via online tools.
Flexible working hours with occasional deadlines requiring high availability.
Opportunity to work on innovative projects with a global impact.
Benefits :
Competitive salary
Flexible work hours and the option for remote work.
Opportunities for professional development and continued education.
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  • Arlington, Texas, United States

Compétences linguistiques

  • English
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