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Signal Processing & AI Engineer

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Onsite

Signal Processing & AI Engineer

Ethosia

Signal Processing & AI Engineer

Skills

PythonMATLABData AnalysisMachine LearningAI

23 days ago

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Important information


Contract type:

Permanent

Location:

Herzliya, Israel

Work mode:

Onsite

Published on:

30 September 2026

What they need


Description

we are looking for a Signal Processing & AI Engineer to join our dynamic team. You will work on innovative projects that integrate signal processing techniques with cutting-edge AI technologies to solve complex problems.

Responsibilities:

  • Develop and implement advanced signal processing algorithms.
  • Collaborate with cross-functional teams to design AI-driven solutions.
  • Analyze and interpret large datasets to improve system performance.
  • Optimize algorithms for real-time applications.
  • Contribute to technical documentation and presentations.
  • Participate in code reviews and provide constructive feedback.

Key Responsibilities:

  • Research and analyze modern AI systems and architectures, including LLMs, VLMs and other emerging model architectures.
  • Research, implement and benchmark models to understand their algorithmic behaviour and system-level performance.
  • Identify compute, memory, bandwidth and latency bottlenecks through profiling and benchmarking.
  • Optimize algorithms for efficient mapping to hardware architectures.
  • Perform quantization and reduced-precision optimization.
  • Develop and analyze fixed-point implementations.

Requirements:

  • Bachelor's degree in Electrical Engineering, Computer Science, or a related field.
  • 3-5 years of experience in signal processing and AI development.
  • Proficiency in programming languages such as Python, C++, or MATLAB.
  • Strong understanding of machine learning techniques and frameworks.
  • Experience with data analysis and statistical modeling.
  • Familiarity with real-time processing and embedded systems.
  • Excellent problem-solving and analytical skills.
  • Hands-on, hard-working, self-driven and independent approach

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