Senior Audio Algorithm Expert

Beijing Foreign Enterprise Management Consultants Co.,Ltd.; Singapore; On-site; SGD 180,000 - 280,000; Full time

Job summary

Huawei is seeking a Senior Audio Algorithm Expert to lead the design and deployment of edge-side audio systems on constrained hardware, including TWS earphones, laptops and IoT devices. You will own architecture, optimize latency, and collaborate across hardware, firmware, and software teams.

The role demands a PhD or exceptional Master’s, strong background in DSP and embedded audio, and hands-on experience deploying models on edge devices with RTOS/embedded Linux.

Qualifications

• PhD or exceptional Master’s in CS/EE/Acoustics or related field.
• Extensive hands-on edge-side / embedded audio algorithm development with production-ready delivery.
• Strong expertise in Fourier analysis, adaptive filtering, and psychoacoustic modeling.

Responsibilities

• Lead architecture design for low-power, low-latency audio algorithms on embedded/edge devices.
• Deploy and optimize algorithms on DSP/ARM Cortex-M platforms with RTOS/embedded Linux.
• Collaborate with hardware, firmware, and platform teams to optimize latency and memory usage.
• Mentor engineers and translate research into scalable product solutions.

Skills

Embedded audio

C/C++

Python

DSP expertise

Audio signal processing

Education

PhD in CS/EE/Acoustics or exceptional Master’s degree

Tools

PyTorch

TensorFlow

ONNX

FreeRTOS/Zephyr

embedded Linux

Job description

On behalf of Huawei, a world-renowned information and communication technology company, we are seeking passionate and talented individuals to join our team as Senior Audio Algorithm Expert.

Role Overview

We are seeking a Senior Audio Algorithm Expert to lead the design and development of low-power, low-latency, real-time audio algorithms for edge-side and embedded platforms. This role focuses on smart terminals such as TWS earphones, laptops, and IoT devices, bridging advanced audio algorithms with constrained hardware systems at scale.

Core Responsibilities

1. Edge-Side Audio Algorithm Architecture

• Lead the architecture design and implementation of low-power, low-latency audio algorithms for embedded and edge devices.
• Take technical ownership in one or more of the following domains:
• Speech Enhancement: noise suppression, echo cancellation, multi-microphone array processing
• Wearable Audio Systems: Active Noise Control (ANC), transparency mode, hearing enhancement, motion-aware audio features
• Intelligent Voice Interaction: ASR front-end processing, TTS enhancement, voice separation, speaker recognition
• Micro-Acoustic Modeling: nonlinear compensation for miniature speakers and microphones

2. Embedded Optimization & Deployment

• Deploy and optimize audio algorithms on resource-constrained platforms (DSP / NPU / ARM Cortex-M).
• Design collaborative architectures across algorithms, hardware, and firmware, optimizing power consumption, latency, and memory usage in real-time systems (RTOS / embedded Linux).
• Lead edge-side AI model optimization, including quantization, compression, and acceleration (e.g., INT8 / FP16, pruning), ensuring production-level performance and stability.

3. Cross-Functional & System-Level Collaboration

• Work closely with hardware and acoustic teams on system design, including MEMS microphone selection, acoustic tuning, and speaker system optimization.
• Collaborate with platform and connectivity teams to optimize audio performance over Bluetooth LE Audio and Wi-Fi in end-to-end products.
• Provide technical guidance and mentorship to senior and junior engineers within the audio algorithm team.

4. Technical Leadership & Innovation

• Track and evaluate state-of-the-art audio research (e.g., ICASSP, INTERSPEECH, IEEE TASLP) and translate research outcomes into practical, scalable product solutions.
• Define mid- to long-term technical roadmaps for edge-side audio systems (e.g., hybrid AI + DSP architectures).

Qualifications

Required Technical Background

• PhD (or exceptional Master’s degree) in Computer Science, Signal Processing, Electrical Engineering, Acoustics, or a related field.
• Extensive hands-on experience in edge-side / embedded audio algorithm development, with a proven record of delivering production-ready systems.
• Strong expertise in audio signal processing, including:
• Fourier analysis, subband processing, active noise control, hearing-aid algorithms
• Adaptive filtering (LMS / NLMS), psychoacoustic modeling
• Solid experience with embedded platforms and real-time systems:
• RTOS (e.g., FreeRTOS, Zephyr) and/or embedded Linux
• DSP architectures (e.g., Cadence / Tensilica or similar)
• Proficiency in C/C++ and Python and/or MATLAB, with the ability to independently develop, debug, and optimize edge-side algorithms.
• Familiarity with deep learning frameworks (PyTorch / TensorFlow / ONNX) and experience deploying models on edge devices.
• Demonstrated mass-production experience in consumer audio products (e.g., ANC algorithms for TWS earphones).

Industry & Domain Knowledge

• Solid understanding of audio-related standards and ecosystems (e.g., ITU-T, AES, MPEG).
• Experience working with mainstream audio chip platforms (e.g., Qualcomm/CSR, TI, MediaTek) or FPGA-based prototyping flows.
• Strong sensitivity to audio quality, balancing subjective listening evaluation with objective metrics (SNR, PESQ, THD+N, etc.).

Preferred Qualifications (Bonus Points)

• End-to-end ownership experience in audio algorithm design for edge-side SoC platforms (e.g., BES or similar).
• Granted patents or significant open-source contributions (e.g., Kaldi, WebRTC, SPTK).
• Strong performance in international audio challenges (e.g., DCASE, MLSP).
• Multilingual speech processing experience (Mandarin, English, dialects).
• Experience with algorithm–hardware co-design, including optimization for dedicated audio accelerators.