Principal Audio DSP & Edge Computing Architect

SUMMARY:
Our client is  seeking a Principal Audio DSP & Edge Computing Architect to own the full audio processing pipeline and edge-computing architecture.
You will design and implement next-generation active noise cancellation (ANC), spatial audio systems, and edge AI features while integrating biometric and flight telemetry data into a unified real-time system.
This role sits at the intersection of DSP, embedded Linux systems, and AI-driven audio processing.

POSITION INFO:

Required Experience & Skills

• MSc or PhD in Electrical Engineering, DSP, Acoustics, or related field
• 4+ years’ experience in embedded Linux and systems programming (C/C++, Python)
• Proven experience in active noise cancellation (ANC) product development
• Strong understanding of adaptive filtering (LMS, NLMS, RLS) and acoustic feedback systems
• Experience with audio DSP platforms (Analog Devices, Qualcomm or similar)
• Strong background in real-time audio processing and low-latency systems
• Experience with machine learning for audio (CRN, RNN, LSTM, or similar)
• Knowledge of spatial audio (HRTF, Ambisonics, 3D audio systems)
• Strong experience with BLE, telemetry systems, and embedded networking protocols
• Proficiency in MATLAB/Simulink, Python, and C/C++
• Aviation, drone, or aerospace audio systems experience
• Embedded AI / edge inference deployment (NPU, TensorFlow Lite)
• Experience with MAVLink or flight telemetry systems
• Understanding of aviation acoustic environments and noise profiles
• Experience working with safety-critical or real-time embedded systems

Key Responsibilities

• Design and develop advanced Deep ANC and spatial audio systems
• Program and optimize audio DSPs (e.g., Analog Devices ADAU series) using SigmaStudio or C/C++
• Develop embedded Linux applications (C++ / Python) on edge compute platforms (NXP i.MX8M / CM4 class)
• Integrate multi-stream data (audio, flight telemetry, biometrics) into a synchronized system timeline
• Develop real-time speech enhancement and noise suppression models (CRN, TinyML, TFLite)
• Build local edge AI features including wake-word detection and audio intelligence processing
• Develop telemetry ingestion systems (MAVLink, BLE, sensor streams)
• Work closely with hardware teams on sensor integration (biometrics, environmental data)
• Support design of crash-safe data logging (AeroVault™ system)
• Develop local gateway and sync systems for post-flight data transfer (AeroSync™)