台北市中正區2年以上專科以上
We are seeking a talented and passionate Audio AI Engineer to join our team. You will be responsible for developing, training, and deploying cutting-edge AI models for real-time and audio noise reduction. Your work will directly impact the clarity and quality of our products, from teleconferencing and communication tools to creative audio production and media.
The ideal candidate has a strong background in deep learning, a solid understanding of digital signal processing (DSP) fundamentals, and a keen ear for sound. You will collaborate with a cross-functional team of researchers, software engineers, and product managers to bring innovative audio solutions to life.
# Responsibilities
1. Design, develop, and train deep learning models (e.g., neural networks) specifically for audio denoising, dereverberation, and speech enhancement.
2. Curate, manage, and preprocess large-scale audio datasets for model training and evaluation. This includes collecting, cleaning, and labeling noisy and clean audio pairs.
3. Optimize AI models for performance, latency, and resource efficiency, ensuring they can run effectively on various platforms, including cloud servers, mobile devices, and embedded systems.
4. Stay up-to-date with the latest research in audio signal processing, machine learning, and generative AI for audio. Explore and prototype new algorithms and techniques to push the boundaries of audio quality.
5. Work closely with the software engineering team to integrate production-ready models into our software and services. Partner with product and design teams to understand user needs and translate them into technical requirements.
6. Develop robust evaluation metrics and conduct rigorous testing (both objective and subjective listening tests) to ensure the denoising models meet high-quality standards.
7. Diagnose and resolve technical issues related to audio processing pipelines and AI model performance.
# Requirements
1. Bachelor's, Master's, in Computer Science, Electrical Engineering, Signal Processing, or a related technical field.
2. Proven experience in a role focused on machine learning, with a specialization in audio, speech, or signal processing.
3. Strong proficiency in Python is a must. Experience with C++ is a plus, especially for low-latency, real-time applications.
4. Hands-on experience with deep learning frameworks such as PyTorch or TensorFlow.
5. A solid theoretical and practical understanding of digital signal processing (DSP) concepts, including time-frequency analysis, filter design, and spectral processing.
6. Familiarity with audio editing software like Audacity, Pro Tools, or Adobe Audition for data inspection and analysis.
7. Proficiency with Git.
# Preferred Qualifications
1. Experience in a production environment deploying machine learning models into live systems.
2. Knowledge of specific audio denoising techniques and models (e.g., RNNoise, WebRTC, U-Net architectures for audio).
3. Experience with real-time audio systems and APIs.
4. A background in audio engineering or a related field, with an excellent ear for sound quality.
5. Strong mathematical foundation in linear algebra, probability, and statistics.
6. Experience with cloud platforms (AWS, GCP, Azure) and MLOps pipelines.
# Soft Skills
1. Excellent problem-solving and analytical skills.
2. Strong communication and collaboration abilities, with the capacity to explain complex technical concepts to non-technical stakeholders.
3. A passion for audio and a creative mindset for solving difficult audio challenges.
4. Ability to work independently and as part of a highly collaborative team.
5. Proficiency in both English and Chinese, written and spoken.