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Tier-1 company and metro location but niche embedded audio DSP skillset limits broad applicant competition.
Highly specialized automotive audio DSP and embedded ML skills limit cross-industry transferability.
Explicit 7-8 years, ADI DSP, embedded C/C++, and automotive domain requirements create strict filters.
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Develop and productize automotive in-car infotainment audio algorithms including AEC, RNC, PSZ, ICC, voice activity detection, and trigger word recognition.
Own the full algorithm lifecycle from requirements interpretation, design, simulation, development, validation, tuning to embedded implementation on ADI DSP and ARM-based SoCs.
Integrate and verify audio algorithms within automotive embedded software stacks ensuring real-time performance, collaborating with cross-functional teams, and applying AI/ML methods and AI-enabled tooling for enhancement and productivity.
7-8 years of experience in audio signal processing and AI-enabled algorithm development on embedded platforms.
Bachelor’s or Master’s degree in Electrical/Electronics & Communication, Computer Science, Signal Processing, Embedded Systems, or equivalent.
Strong programming skills in Embedded C/C++, with embedded systems fundamentals including RTOS, concurrency, timing, and debugging.
Experience developing and integrating software on ADI DSPs and ARM-based SoCs; capability in algorithm-to-embedded translation with performance optimization; practical AI/ML application in audio processing; use of AI-assisted engineering tools.
Experienced in automotive audio infotainment or cabin audio projects especially in AEC, voice enhancement, noise cancellation, beamforming, or in-car communication.
Demonstrated ability to handle end-to-end embedded algorithm development and optimization on DSP and SoC platforms in production environments.
Comfortable collaborating cross-functionally including customer-facing roles and using AI/ML to improve algorithm robustness and employing AI-enabled productivity tools for engineering lifecycle acceleration.