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Strong Tier-1 brand and metro location, but highly niche embedded audio DSP skillset reduces applicant pool.
Highly specialized embedded audio and automotive DSP expertise limits cross-industry transferability.
Explicit 8–10 years, required embedded DSP, RTOS, C/C++, and automotive audio ML make filters stringent.
Develop, prototype, and productize automotive in-car infotainment audio algorithms, applying AI/ML methods to improve robustness and user experience.
Own full algorithm lifecycle including design, simulation, development, validation, tuning, and embedded implementation on ADI DSP and ARM-based SoC platforms ensuring real-time performance and memory efficiency.
Integrate and verify audio algorithms in automotive embedded software stacks, collaborate with cross-functional teams, and use AI-enabled tools to enhance engineering productivity and quality.
Bachelor’s or Master’s degree in Electrical/Electronics, Computer Science, Signal Processing, Embedded Systems or equivalent.
8-10 years of experience in audio signal processing and AI-enabled algorithm development on embedded platforms.
Strong programming skills in Embedded C/C++ and exposure to AI/ML methods applied to automotive noise cancellation/audio applications.
Experience in algorithm-to-embedded translation, real-time performance optimization, and embedded integration on ADI DSPs and ARM-based SoCs.
Deep expertise in automotive audio infotainment software projects and cabin audio use cases such as AEC, voice enhancement, RNC, beamforming, and in-car communication.
Proficient in AI/ML techniques in audio signal processing and comfortable using AI-enabled engineering tools for coding, testing, and documentation.
Demonstrates ownership with ability to handle multiple parallel tasks, rapid prototyping, and collaborate effectively with cross-functional and customer-facing teams.