דרושים » הנדסה » Algorithm and DSP Engineer

Requirements:
B.Sc. in Electrical Engineering or equivalent - Must, M.Sc. - advantage
Design and implement signal processing and Communication algorithms in C/C++ for real-time systems
5+ years of software development experience in both high level languages (matlab, python) and low level languages (C++)
Experience with software-defined radio (SDR) / RF / DSP - advantage
Knowledge of wireless communication protocols and satellite communication - advantage.

Requirements:
Minimum Qualifications
BSc in Electrical Engineering, Computer Engineering, Acoustics, Audio Engineering, or a related field.
7+ years of experience in audio testing, voice quality evaluation, or acoustic system validation.
Proven experience working within or alongside professional audio/acoustic test laboratories.
Demonstrated ability to design repeatable, controlled test environments and methodologies.
Experience with both objective measurement tools and subjective listening evaluation protocols.
Strong system-level understanding with the ability to isolate quality issues to specific processing stages.
Deep understanding of audio signal processing fundamentals - frequency domain analysis, filtering, spectral characteristics, and time-domain behavior
Hands-on experience with voice quality measurement tools and standards (POLQA, PESQ, 3QUEST, ETSI standards).
Familiarity with HEAD acoustic test equipment - measurement microphones, artificial heads (HATS), mouth simulators, and anechoic/semi-anechoic chamber setups.
Strong proficiency in Python for test automation, data analysis, audio signal processing, and framework development.
Experience with audio acquisition systems, DACs/ADCs, and real-time audio streaming architectures.
Understanding of latency measurement methodologies in real-time audio systems.

Preferred Qualifications
MSc in Acoustics, Audio Signal Processing, Electrical Engineering, or a related discipline - considered a significant advantage.
Experience with speech recognition systems and WER evaluation methodologies.
Background in psychoacoustics or subjective audio evaluation research.
Experience with environmental simulation lab design and commissioning.
Knowledge of ITU-T P-series recommendations and ETSI test specifications.

Requirements:
Minimum Qualifications
5+ years of experience in communication/signal processing/ranging.
Deep understanding of RX and TX MODEM and RF chains.
Deep knowledge of Wireless communication systems.
System level understanding - ability to comprehend and contribute to multi-disciplinary process employing HW, signal processing and SW.
Analytical skills - ability to triage a problem root cause in a complex system
Familiarity and ability for SW/FW coding.
Familiarity with lab test equipment.
BSc/MSc in Electrical Engineering/Computer Engineering or relevant fields.

Preferred Qualifications
Understanding of MAC systems - an advantage.

Requirements:
The Mindset: Passion and motivation for finding vulnerabilities in complex systems.
Reverse Engineering: High-level proficiency in IDA Pro, Ghidra, etc., specifically targeting non-x86 architectures (ARM, MIPS, RISC-V).
Low-Level Mastery: 4+ years of experience in C/C++ and Assembly, with a deep understanding of memory management, heap/stack protections, and OS internals.
System Knowledge: Comprehensive understanding of the boot process and hardware-software abstraction layers.
Advantages
RF Security: Experience with Software Defined Radio (SDR), signal processing, and protocol analysis of wireless communications.
Education: Bachelors degree in Physics, Electrical Engineering, or Computer Science.
Military Background: Graduate of an elite technological unit in the IDF.

Requirements:
Minimum Qualifications
BSc in Electrical Engineering, Computer Engineering, Physics, or a related field.
7+ years of extensive experience in embedded systems, electro-optical sensor integration, or related disciplines.
Strong Python proficiency - automation frameworks, data analysis, instrument control, and test development.
Demonstrated experience with HW/SW automation, design control, and development methodologies.
Solid understanding of camera and laser sensor technologies and associated interface protocols.
Proven ability to bridge the gap between physics-level understanding and engineering implementation.
Deep understanding of electro-optical sensor principles - including photodetection, quantum efficiency, noise characterization (read noise, dark current, shot noise), and signal-to-noise ratio analysis.
Experience with optical test bench setups: integrating spheres, collimators, laser sources, spectral filters, and beam profiling equipment.
Familiarity with LiDAR / ToF sensor technologies - including timing resolution, range accuracy, and multi-path interference analysis.
Knowledge of image sensor characterization methodologies.
Experience with radiometric and photometric measurements and calibration procedures.
Understanding of laser safety classifications, optical power measurement, and wavelength characterization.
Ability to define and execute environmental and stress testing protocols for optical sensor assemblies.

Preferred Qualifications
Advanced degree (MSc or PhD) in Physics, Electro-Optics, or Electrical Engineering.
Experience with embedded firmware development or firmware-hardware co-validation.
Familiarity with CI/CD pipelines for hardware validation environments.

Requirements:
Minimum Qualifications
BSc in Electrical Engineering, Computer Engineering, Mechanical Engineering, Physics, or a related field - advanced degree strongly preferred.
7+ years of experience in environmental testing, sensor characterization, or embedded system validation.
Strong Python proficiency - automation, data analysis, instrument control, and framework development.
Proven experience bringing up sensors and subsystems on new development platforms.
Hands-on experience with HW/SW automation design, control systems, and development workflows.
Strong system-level vision - ability to comprehend the full system architecture and understand how individual sensor components interact within the broader product context.
System-to-component testing capability - proven ability to conduct system-level validation while diving deep to the component level for root-cause analysis, failure isolation, and detailed characterization.
Strong experience in environmental test design and execution for electro-optical systems.
Proficiency in system-level Test firmware development for embedded sensor platforms.
Demonstrated ability to architect and implement automation frameworks (Python-based) supporting: Instrument control and data acquisitio; API development for system-level integration; End-to-end test orchestration and regression capabilities.
Knowledge of optical performance metrics - MTF, field of view, distortion, stray light, and dynamic range under varying environmental conditions.
Familiarity with environmental simulation equipment - solar simulators, rain chambers, thermal chambers, vibration tables, and motion stages.
Understanding of laser sensor behavior under environmental stress - including atmospheric scattering, thermal drift, and background noise rejection.
Experience with sensor alignment and calibration methodologies in controlled laboratory settings.

Preferred Qualifications
MSc in Physics, Electro-Optics, Electrical Engineering, or a related discipline - considered a significant advantage.
Experience working with VXcl platforms and Sony image sensors - configuration, bring-up, characterization, and integration.
Experience developing custom test fixtures and mechanical setups for optical evaluation - including design, specification, and validation of purpose-built environmental and alignment rigs.

Requirements:
Minimum Qualifications
MSc or PhD in Computer Science, Electrical Engineering, Physics, Applied Mathematics, or a related field.
Hands-on experience with machine learning and deep learning.
Proficiency in Python and PyTorch or a similar deep learning framework.
Strong communication skills and proficiency in English.
Ability to work well in a collaborative, highly cross-functional, and fast-paced environment.

Preferred Qualifications
Solid understanding of physics and the ability to apply physical principles to machine learning problems.
Strong understanding of optimization, model training, validation, and debugging of neural networks.
Experience with scientific computing libraries such as NumPy, SciPy, pandas, or similar tools.

Requirements:
Minimum Qualifications
Minimum: Master's degree (MSc) in one of the following fields: Computer Science or Mathematics with specialization in Machine Learning, Signal Processing and Telecommunications Engineering.
Real-time Systems: Experience in real-time computing constraints and low-latency system design.
Machine Learning: Deep understanding of ML algorithms, particularly those suitable for real-time applications (online learning, federated learning, reinforcement learning, neural networks).
Wireless Communications: Strong foundation in wireless communication principles, protocols.
Programming: Proficiency in Embedded C, Python, MATLAB, C++, and ML frameworks.
Optimization: Experience with convex optimization, resource allocation algorithms, and constraint satisfaction problems.
Research Experience: Demonstrated track record of independent research through publications, patents, or significant project contributions.
Knowledge of edge computing and distributed ML systems is advantageous.
Personal Attributes: Self-Motivated: Ability to work independently, set research priorities, and drive projects from conception to completion.
Analytical Thinking: Strong problem-solving skills with ability to tackle complex, multi-disciplinary challenges.
Innovation-Oriented: Creative approach to research with ability to think outside conventional boundaries.
Communication Skills: Excellent written and verbal communication skills for technical documentation and presentations.
Collaborative Spirit: Ability to work effectively in cross-functional teams while maintaining independent research focus.

Preferred Qualifications
Ph.D. in related field.

Requirements:
Minimum Qualifications
BSc in Electronics Engineering, Mechanical Engineering, Computer Science, or Physics.
At least 5 years of experience as a system engineer of multi-disciplinary systems, delivering products from PoC to mass production phase.
Detailed understanding of optical sensing systems and modules design: image sensors, laser emitters, optical elements, mechanics, assembly processes, laser drivers, SoC computation and interfaces.
Experience defining and tracking system requirements and specifications from system level, through sub-modules and components.
Expertise in system level modeling/simulation, image/signal processing and large scale data analysis in Matlab and/or Python.
Great interpersonal skills - team player with the ability to collaborate across multiple groups.

Preferred Qualifications
MSc/PhD in a relevant field (EE, ME, CS, or Physics) or equivalent.
Hands on lab experience with optical setups and/or electrical equipment.
Experience with laser safety and compliance domains.
Experience in the consumer electronics industry and vendors.