
Aigc Audio Algorithm Specialist
3 days ago
**Job Overview**:
As an AIGC Audio Specialist, you will be at the intersection of audio technology and creative arts, responsible for pushing the boundaries of music and sound generation technology. You will design and implement advanced audio generation models capable of understanding, creating, and optimizing music and various sound effects, providing users with unprecedented personalized audio experiences. Additionally, you will stay abreast of the latest research developments in the audio technology field to ensure our solutions remain industry-leading.
**Responsibilities**:
- Research and optimize large-scale audio generation models, including music synthesis, sound effect generation, and style transfer.
- Explore and experiment with the latest research findings, converting them into practical product features such as automatic accompaniment generation and sound emotion simulation.
- Collaborate with cross-functional teams including data scientists, software engineers, and product designers to ensure smooth project progress.
- Participate in domestic and international academic conferences to exchange ideas with top industry talent.
- Regularly assess model performance, optimize algorithms for efficiency, reduce resource consumption, and ensure model stability and scalability.
- Assist sound designers in building large audio models.
- Develop unimodal and multimodal models.
- Responsible for audio technology development, algorithm implementation, and optimization in audio and video products.
- Analyze and process large-scale audio materials.
- Maintain audio frontend quality algorithms to ensure product audio quality.
**Requirements**:
- Bachelor’s degree or higher in Computer Science, Signal Processing, Electronic Engineering, or related fields.
- Proficient in deep learning frameworks (such as TensorFlow, PyTorch) with experience in building complex audio generation models.
- In-depth understanding of audio signal processing, music theory, and acoustic principles.
- Ability to read and understand English scientific literature and stay highly informed on the latest research developments in audio technology.
- Deep understanding and practical experience in AIGC audio technology, SUNO, Stable Audio, particularly in audio generation and processing technologies, with a preference for those familiar with machine learning and deep learning algorithms.
- Extensive experience with Qwen Audio, and clear understanding of tasks related to Sound/Music&Song in Qwen Audio.
- Knowledge of implementing online audio libraries (cloud-based), proficiency in handling audio data in PyTorch, including audio classification and processing, and building custom data loaders for specific scenarios to approve data and train models.
- Understanding of CLAP audio model encoder.
- Familiarity with common enhancement algorithms such as noise reduction, echo cancellation, dereverberation, array signal processing, adaptive signal processing, and active noise cancellation.
- Knowledge of spatial audio, such as 7.1.4, and principles of Wwise.
- Understanding of cost functions (MLM, MSP, SOP) and error values.
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