Arbe Careers

Radar Algorithm Developer

Tel Aviv · Full-time · Senior

About The Position

By powering next-generation road safety, we’re achieving something remarkable. Built on our proprietary chipset, Arbe ultra high-resolution 4D imaging radar is disrupting vehicle sensor technology to drive the autonomous revolution forward. We are a fast growing, well funded start-up, developing E2E solutions including RF, ASIC, AI and Post-Processing algorithms.

Our elite Algorithm Team is responsible for developing innovative and ingenious solutions to challenges that arise from automotive sensor radar resolution and data quality improvements. We’re seeking for a talented Radar Algorithm Developer to join our team to help further refine our efforts as we together create the next generation of radar that will include deep learning algorithms.

Responsibilities

  • Create groundbreaking processing algorithms using signal processing, deep learning and other techniques
  • Simulate and test new algorithms
  • Research the latest publications in radar technology, signal processing, and deep learning
  • Tackle non-trivial data to identify problems and suggest solutions for the signal processing (RADAR) algorithms
  • Design experiments in the lab and in real-world scenarios
  • Shadow the software development of the algorithms solutions 
  • Collaborate with our software, system, integration, and hardware teams
  • Work with the development team to implement algorithms in real-time environments

Requirements

  • M.Sc. or higher in physics / math / computer science / electrical engineering
  • At least one year of academic or work experience in radar or special signal processing, including topics like Fourier transforms and FFT-s, S/N analysis, sampling, FMCW, doppler ambiguity etc
  • Hands on experience in MATLAB or Python
  • Strong mathematical skills
  • A problem solver with strong analytical skills
  • A team player with the ability to work independently
  • Fast learner
  • Motivated and creative

Preferred Qualifications

  • Knowledge of radar systems
  • Academy or work experiences in creating innovative deep learning networks

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