Senior Software Engineer - Automotive Audio Algorithms

About the role

Analog Devices is hiring a Senior Software Engineer to define, develop and productize automotive in-car infotainment audio algorithms across the cabin audio signal chain. The role covers algorithm design, embedded implementation on ADI DSP and ARM-based SoC platforms, and integration into automotive software stacks, with a focus on real-time performance and memory efficiency.

Key responsibilities

• Develop algorithms such as Acoustic Echo Cancellation, acoustic and voice cancellation, Road Noise Cancellation, Personalized Sound Zones, In-Car Communication, voice activity detection and trigger word recognition.
• Apply AI/ML methods where beneficial, including model-assisted estimation, adaptive scene classification, learning-based enhancement and dataset creation for training.
• Own the full algorithm lifecycle: requirements, design, simulation, development, validation and tuning.
• Implement and optimize algorithms on ADI DSP and ARM-based SoC platforms, and integrate them into automotive embedded software stacks.
• Contribute to system-level integration and verification of real-time automotive products, debugging issues across algorithm, firmware and platform layers.
• Work with systems, firmware, QA, product and customer teams, and document work products in line with structured development expectations such as ASPICE.

Required profile

• Bachelor's or Master's degree in Electrical/Electronics & Communication, 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 fundamentals in signal processing and algorithmic thinking; MATLAB-based modeling is valuable.
• Ability to work independently, handle change requests and iterate quickly through rapid prototyping.
• Strong problem-solving, communication and self-starting skills; 10% travel required, day shift.

Required skills

• Embedded C/C++ with a disciplined approach to real-time, performance-critical development.
• Exposure to AI/ML methods and tools for automotive noise cancellation and audio applications.
• Embedded systems fundamentals: RTOS concepts, concurrency, timing and debugging.
• Experience developing software on ADI DSPs and ARM-based SoC/ASSP platforms, including floating/fixed-point, latency budgeting and memory/performance profiling.
• Preferred: background in automotive audio infotainment, and hands-on experience with AEC, RNC/ANC, beamforming and sound zones.
• Expected: practical use of AI/ML techniques in audio and AI-enabled engineering tools for coding, testing and documentation.