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About the Role:

We are looking for an experienced and hands-on Senior C/C++ Real-Time Embedded Software Engineer (Embedded & RF) to drive the development of our mm-wave radar product line for safety-critical railway applications. You will be responsible for real-time embedded software running on embedded Linux and RTOS platforms (including FreeRTOS), working closely with RF, algorithm, hardware, and system engineers to deliver robust, high-performance systems. This role is ideal for a senior embedded engineer with strong real-time experience, who enjoys being close to hardware and collaborating across multiple disciplines. This is a hybrid position in our Rehovot office.

What You’ll Be Doing:

· Design, develop, and maintain real-time embedded software in C/C++ for radar and RF-based embedded systems

· Implement and optimize low-level drivers, BSPs, and hardware abstraction layers for microcontrollers, SoCs and RF front ends

· Develop software for both Embedded Linux and RTOS-based systems

· Design and integrate the control of RF front ends via SPI, I2C, GPIO

· Implement multi-threaded application under strict RT and low latency constraints

· Support board bring-up, HW/SW integration, and debug activities

· Work closely with RF engineers, algorithm team, hardware team, and system engineers

· Follow software engineering best practices, including code reviews, unit/integration testing, CI/CD for embedded targets

Requirements:

· B.Sc. in Computer Science, Software Engineering, Electrical Engineering, or related field.

· 5+ years of hands-on experience in C and/or C++ development in embedded/ real-time environments

· Strong experience with Embedded Linux:

o Cross compilation and build systems (e.g., CMake, Make, Yocto/Buildroot)

o User-space applications; kernel driver experience is an advantage

· Experienced working directly with microcontrollers, SoCs (e.g., ARM Cortex-M/ Cortex-A)

· Knowledge with ROS/ROS2, including distributed node design and integration in real-time data pipelines

· Strong debugging skills in embedded and RF environments

· Strong background in real-time and low-latency data processing and integration with hardware/software interfaces

· Familiarity with FPGA integration and communication protocols

· Excellent problem-solving skills, a “hands-on” mindset, and strong communication skills in English (spoken and written).

· Familiarity with Python for tooling, test automation, or data analysis.

Position Overview

We’re looking for an experienced, hands-on Senior Perception Algorithm Engineer to lead the development of advanced perception capabilities for real-world, safety-critical environments.

This is a hands-on and delivery-oriented position that sits at the core of NIART’s perception stack, combining data from multiple sensing modalities, including cameras, Radar, LiDAR, geo-spatial data, GIS layers and more.

The position is a full-time, hybrid role based primarily in Rehovot, Park HaMada, conveniently located next to the train station.

YOU ARE: thriving when taking full, end-to-end ownership and seeing your algorithms deployed and working in the real world; capable to both design the algorithmic approach and also implement it, test it on field data and validate performance, while balancing state-of-the-art methods with practical solutions where needed.

Responsibilities

· Perception & Algorithm Development: Design, develop, and optimize algorithms for real-world perception systems, including detection, tracking, scene understanding, geometry-based methods, and learning-based approaches for sensor fusion, radar-signals analysis, computer vision, classification, mapping, and anomaly detection.

· Multimodal Sensor Fusion: Work with diverse sensing modalities, including RGB, IR, radar, and additional sensors or signal sources. Analyze, preprocess, align, validate, and fuse data from multiple sources to improve system robustness and performance.

· End-to-End Ownership: Own algorithmic components from problem definition and data analysis through implementation, validation, integration, and performance monitoring.

· Data & Validation: Define labeling requirements, review datasets, perform quality checks, mine edge cases, build benchmarks, and analyze model, data, and system failure modes.

·  Tooling & Automation: Develop scripts and pipelines for data processing, training, evaluation, experiment tracking, visualization, and reporting.

· Lab & Field Validation: Participate in sensor setup, calibration, data collection, field experiments, debugging, and system-level performance analysis.

Qualifications

· B.Sc. in Electrical Engineering, Computer Science, Computer Engineering, or a related field; M.Sc. is an advantage.

· 6+ years of hands-on experience in perception, sensor fusion, multi-object tracking, signal processing, computer vision, deep learning, robotics, autonomous systems, or related domains.

· Strong Python proficiency and experience writing production-quality code using PyTorch/TensorFlow, OpenCV, NumPy, and Scikit-learn, or similar tools.

· Proven experience developing, validating, and deploying algorithms or neural-network models for real-world sensing or perception applications, including detection, segmentation, tracking, sensor geometry, calibration, 3D perception, or image-to-world transformations.

Hands-on experience beyond standard computer vision is required, with at least one additional sensing modality or signal source such as radar, sonar, LiDAR, time-series sensor data, or other sensor-based signals.

· Experience with sensor fusion, multimodal perception, mapping or localization is a strong advantage.

· Experience with radar perception, radar signal processing, or radar-based classification – advantage

· Experience with GIS tools, map layers, spatial databases, or geo-data pipelines -advantage.

· Experience with image anomaly detection is an advantage.

· Experience working on autonomous systems, robotics, defence, mobility, smart infrastructure, or safety-critical systems – advantage.

· Experience with TensorRT, CUDA, runtime optimization, or embedded deployment – advantage

· Experience deploying algorithms to edge devices, embedded platforms, or real-time systems – advantage.

· Experience with Linux, Git, and collaborative development workflows.

· Experience building data-processing, evaluation, automation, or experiment-management pipelines is an advantage.

Skills

· Applied perception engineering mindset — able to turn real-world sensing challenges into practical, testable, and deployable solutions.

· Independent, accountable, and proactive, with a strong “own-it” mindset.

· Strong problem-solving skills and a structured approach to debugging and validation.

· Strong communication skills and ability to work with cross-functional teams across algorithms, software, systems, hardware, and product.

· Team-player with strong attention to detail and commitment to high-quality engineering standards.

About the Role:

We are looking for an experienced and hands-on Radar Algorithm Engineer to join the development of our high-frequency MIMO radar product line for safety-critical railway applications.

You will be responsible for developing, implementing, and validating advanced radar signal processing algorithms, working closely with RF, embedded software, hardware, and system engineers to deliver robust, high-performance radar systems. This role is ideal for an engineer with strong radar fundamentals, practical algorithm development experience, and the ability to take research ideas from concept to real-world implementation.

What You’ll Be Doing:

· Develop and implement advanced radar signal processing algorithms for high-frequency MIMO radar systems.

· Work on spatial processing, angle estimation, beamforming, detection, parameter estimation, and target characterization.

· Analyze radar data from lab, field, and railway environments to improve system performance and robustness.

· Design and validate algorithms for safety-critical railway applications, including object detection and scene understanding.

· Work closely with RF engineers on waveform design, antenna configuration, calibration, and RF system behavior.

· Collaborate with embedded software engineers to support real-time implementation and integration of radar algorithms.

· Support system integration, field testing, debugging, and performance evaluation.

· Develop simulation, analysis, and visualization tools in Python.

· Translate research concepts into practical algorithms that can run in real radar systems.

· Participate in defining radar processing architecture, performance metrics, and validation methodologies.

Requirements:

· Bachelor’s degree in electrical engineering, Mathematics, Physics, or a related engineering field.

· 3+ years of hands-on experience in radar signal processing, including spatial processing, parameter estimation, and advanced radar algorithm development.

· Strong understanding of radar processing fundamentals, including detection, estimation, tracking concepts, and signal analysis.

· Proven experience developing and implementing algorithms in Python.

· Practical experience with radar data analysis, visualization, and real-time or offline processing workflows.

· Experience with ML/DL based radar perception, and radar-based classification – advantage

· Experience working in autonomous systems, robotics, defence, mobility, smart infrastructure, or safety-critical systems – advantage.

Skills

· Applied engineering mindset – able to turn real-world sensing challenges into practical, testable, and deployable solutions.

· Independent, accountable, and proactive, with a strong “own-it” mindset.

· Strong problem-solving skills and a structured approach to debugging and validation.

This is a hybrid position in our Rehovot office.