SAR Remote Sensing Engineer

Harmattan Ai
Paris, France
On-site

Who this role is best for

Geared toward candidates with a strong background in SAR remote sensing and machine learning, comfortable with real-time implementation and field validation.

Best fit for

  • Candidates with advanced degrees in signal processing and hands-on experience in deploying algorithms to real hardware
    — “Experience taking at least one algorithm from prototype to real hardware running on real signals.”
  • Individuals with a deep technical understanding of SAR phenomenology and a track record in multi-modal sensor fusion
    — “Fuse SAR with optical, RF and other data sources to support GNSS-denied operations.”
  • Candidates who can bridge algorithm development and operational field validation in a high-stakes domain
    — “Validate performance on simulated and real-world datasets, in the lab and on field-test campaigns.”

Things to consider

  • Periodic travel to field and lab test locations is a key requirement of the role.
    — “Willingness to travel periodically to lab and field tests.”
  • Candidates must be prepared for defense security vetting as part of the role.
    — “Exposure to GEOINT, ELINT or SIGINT work is a plus, and you are comfortable with defense security vetting.”

How to stand out

  • Highlight experience with SAR polarimetry and coherence in change detection projects.
    — “Lead initiatives using SAR polarimetry and coherence for automated change detection.”
  • Demonstrate expertise in both deep learning and classical machine learning techniques for SAR image segmentation.
    — “Theoretical and practical expertise in machine learning, both deep learning and classical techniques.”
  • Emphasize your experience in porting algorithms from Python to real-time systems.
    — “Port algorithms from Python prototypes to real-time pipelines with software and embedded/FPGA teams.”
  • Demonstrate your ability to create reproducible performance claims through tooling and data labeling.
    — “Build the capture, labelling and replay tooling that makes performance claims reproducible.”
Pace · SteadyCollaboration · MediumAutonomy · HighDecision Impact · Team

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • lead initiatives using SAR polarimetry and coherence for automated change detection
  • design and prototype state-of-the-art machine learning models for SAR image segmentation
  • develop algorithms for target detection and object classification on SAR data
  • port algorithms from Python prototypes to real-time pipelines with software and embedded/FPGA teams
Typical background
Master’s or PhD in electrical engineering, telecommunications engineering, signal processing, applied mathematics or a related field3+ years of experience in radar signal processing or SAR remote sensing

Skills & requirements

Required

Advanced Signal ProcessingMachine LearningSAR Data AnalysisAlgorithm DesignReal-time ImplementationField ValidationMulti-modal SolutionsPorting AlgorithmsCapture, Labelling And Replay ToolingValidating PerformanceFusing SAR With Optical, RF And Other Data SourcesWorking With Radar, Radio, Electronic Warfare And Computer Vision Teams

Preferred

Exposure To Geoint, Elint Or Sigint WorkWillingness To Travel Periodically To Lab And Field Tests

Stack & domain

SAR PolarimetryCoherenceAutomated Change DetectionSAR Image SegmentationTarget DetectionObject ClassificationSAR DataPythonMachine LearningDeep LearningClassical TechniquesEmbedded/fpgaSoftwareReal-time PipelinesCaptureLabellingReplay ToolingPerformance ClaimsRadarRadioElectronic WarfareComputer VisionAlgorithm DesignReal-time ImplementationField ValidationMulti-modal SolutionsPorting AlgorithmsPerformance ValidationSensor FusionField TestsDefense SystemsAutonomous SystemsRF AnalyticsGnss-denied OperationsSAR Remote SensingSignal ProcessingDefense Security Vetting

About the role

Original posting from Harmattan Ai via Ashby

ABOUT US

Harmattan AI is a next-generation defense prime building autonomous and scalable defense systems. Following the close of a $200M Series B, valuing the company at $1.4 billion, we are expanding our teams and capabilities to deliver mission-critical systems to allied forces.

Our work is guided by clear values: building technologies with real-world impact, pursuing excellence in everything we do, setting ambitious goals, and taking on the hardest technical challenges. We operate in a demanding environment where rigor, ownership, and execution are expected.

ABOUT THE ROLE

As SAR Remote Sensing Engineer, you are the subject matter expert on applying advanced signal processing and machine learning to SAR data within our RF analytics team. You own the analytics layer end to end: algorithm design, real-time implementation and field validation on real captures from our own platforms. You will also shape the move toward multi-modal solutions that combine SAR with optical and RF sensor feeds. Cycles are measured in months, and the scope grows with the company.

RESPONSIBILITIES

  • Lead initiatives using SAR polarimetry and coherence for automated change detection.
  • Design and prototype state-of-the-art machine learning models for SAR image segmentation.
  • Develop algorithms for target detection and object classification on SAR data.
  • Fuse SAR with optical, RF and other data sources to support GNSS-denied operations.
  • Port algorithms from Python prototypes to real-time pipelines with software and embedded/FPGA teams.
  • Build the capture, labelling and replay tooling that makes performance claims reproducible.
  • Validate performance on simulated and real-world datasets, in the lab and on field-test campaigns.
  • Work with radar, radio, electronic warfare and computer vision teams to define what the analytics layer needs from each sensor.

CANDIDATE REQUIREMENTS

  • Master’s or PhD in electrical engineering, telecommunications engineering, signal processing, applied mathematics or a related field.
  • 3+ years of experience in radar signal processing or SAR remote sensing.
  • Deep understanding of SAR phenomenology and its information content, including coherence, amplitude, phase and polarimetry.
  • Theoretical and practical expertise in machine learning, both deep learning and classical techniques.
  • Experience taking at least one algorithm from prototype to real hardware running on real signals.
  • Strong Python skills and sound engineering practices (Git, code reviews, testing, documentation).
  • Exposure to GEOINT, ELINT or SIGINT work is a plus, and you are comfortable with defense security vetting.
  • Willingness to travel periodically to lab and field tests.

We look forward to hearing how you can help shape the future of autonomous defense systems at Harmattan AI.

Source: Harmattan Ai careers (Ashby)

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