Perception Algorithms Software Engineer — Radar and Sensor Fusion

At Zadar Labs, we are redefining perception for intelligent systems through high-resolution imaging radar and AI-driven sensing technologies. Our mission is to enable machines to perceive and understand the world more reliably across autonomous systems, robotics, industrial automation, smart infrastructure, and public safety applications.

We are looking for a highly motivated Radar Perception and Sensor Fusion Software Engineer to join our growing engineering team and help build next-generation perception software platforms.

As a Radar Perception and Sensor Fusion Software Engineer, you will design, develop, and deploy algorithms for radar perception and sensor fusion, translating mathematical concepts and experimental prototypes into reliable, real-time software.

You will own algorithm development from problem definition and prototyping through quantitative validation, production implementation, and deployment. Your work will include object detection, clustering, multi-object tracking, sensor fusion, and real-time processing pipelines.

The ideal candidate is a highly capable software engineer with strong C++ and Python skills, practical mathematical foundations, and demonstrated algorithm development experience. We are looking for someone who can formulate a problem, evaluate alternative approaches, understand their assumptions and limitations, and improve solutions through experimentation with real sensor data.

You will work closely with cross-functional teams across perception, robotics, AI, embedded systems, and Dev Ops to deliver robust production-grade solutions. The role involves collaboration with multicultural and globally distributed teams, partners, and customers across different regions and technical domains.

• Design, develop, test, validate, and maintain software modules and algorithms across the perception and robotics stack.
• Develop scalable and maintainable real-time software systems using C++ and Python, with ROS / ROS2 where appropriate.
• Design and improve algorithms for radar perception, sensor fusion, object detection, clustering, and multi-object tracking.
• Analyze recorded and live sensor data to identify failure modes, investigate underlying causes, and improve algorithm performance.
• Apply probabilistic estimation and data association methods, such as Kalman filters, to perception problems.
• Build robust APIs, middleware layers, and processing pipelines for perception systems.
• Optimize software and algorithms for accuracy, robustness, computational cost, and real-time latency.
• Develop tools for debugging, visualization, logging, replay, and performance evaluation.
• Define evaluation metrics and reproducible tests; validate algorithms using recorded datasets, simulation, and real-world testing.
• Work across Linux-based development environments and embedded platforms.

• Develop and improve CI/CD pipelines and automated testing infrastructure.
• Maintain build, release, and deployment systems.
• Debug integration and regression issues across software modules.
• Work closely with engineers to improve software quality, reliability, and scalability.
• Maintain dashboards, reports, and software health monitoring systems.

• Integrate perception software and algorithms with radar sensors, cameras, GPS/IMU systems, and embedded computing platforms.
• Support deployment on NVIDIA Jetson, ARM-based systems, and edge AI devices.
• Develop and maintain Docker-based development and deployment workflows.
• Support software packaging, release management, and deployment automation.
• Assist with field testing and debugging of deployed systems.
• Bachelor’s degree in Computer Science, Electrical Engineering, Robotics, Computer Engineering, or a related field.
• Strong software engineering skills in C++ and Python.
• Demonstrated experience designing, implementing, and evaluating algorithms in perception, robotics, signal processing, computer vision, estimation, or a related field.
• Strong foundations in linear algebra, probability, and statistics, with the ability to apply them to practical engineering problems.
• Ability to formulate problems, compare algorithmic approaches, analyze failure cases using data, and validate improvements quantitatively.
• Experience translating algorithm prototypes into tested, maintainable software.
• Experience with Linux environments, Git-based workflows, and software debugging and…