As a Radar Software Engineer at EDGE, you will be responsible for designing, implementing, and optimizing radar software solutions that align with system performance and functional requirements. Your key responsibilities will include:
- Developing signal and data processing algorithms, such as pulse compression, filtering, target detection, and tracking.
- Optimizing software for real-time execution with minimal latency, ensuring efficient use of CPU, GPU, and memory resources.
- Conducting software testing through simulations and field trials, and analyzing results to validate system performance.
- Developing and maintaining software interfaces to ensure accurate communication between radar hardware and related subsystems.
- Documenting software architecture, design choices, and testing outcomes in a clear and organized manner.
- Collaborating with system engineers, hardware developers, and algorithm specialists to align on project goals and ensure successful integration.
- Identifying technical risks in the development lifecycle and proposing solutions to mitigate delays or performance issues.
- Staying updated on advancements in radar systems, signal processing, and software development best practices.
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Education & Experience:
- Bachelor's or Master’s degree in Computer Science, Electrical Engineering, or a related field.
- A minimum of 5 years of professional experience in software development, specifically within radar or signal processing applications.
- Proven track record of working on real-time embedded systems and performance-critical applications.
- Experience in testing and validating radar systems through both simulation and field testing environments.
Key Skills:
- Strong programming skills in C/C++, Python, or similar languages.
- Solid understanding of digital signal processing (DSP) techniques.
- Hands-on experience with real-time system optimization and resource management (CPU, GPU, memory).
- Familiarity with software development tools such as Git, Jenkins, or similar CI/CD pipelines.
- Experience with GPU programming (e.g., CUDA) is a plus.
- Excellent documentation skills for technical design, system behavior, and testing processes.
- Strong problem-solving, collaboration, and communication abilities.
