Job Description
52 days ago
Job Responsibilities:
1.Responsible for training/inference optimization and performance tuning of key algorithms in cognitive computing fields such as machine learning, deep learning, etc.
2.Lead work in music-related areas such as audio enhancement, content understanding, content generation, multimodal systems, and dialogue systems. Responsible for designing corresponding AI solutions and landing algorithmic model features.
3.Keep abreast of cutting-edge AI technologies, propose innovative methods, and solve business problems in practical music and social application scenarios.
Qualifications:
1.PhD or Master's degree in computer science, mathematics, or related fields. Familiar with fundamental principles of neural networks, recent hot topics such as Attention, Transformer, multimodalities, with experience in development or research in machine learning.
2.Familiar with pre-training models such as BERT series, GPT series, deep learning models like Transformer, and principles/methods of music-related content understanding and content generation. Candidates with experience in combining business requirements are preferred.
3.Experience in practical model development, fine-tuning, and training parameter adjustment. Able to analyze and solve problems encountered during model training.
4.Broad curiosity in various branches of AI technology, good learning ability, and solid development foundation.
1.Responsible for training/inference optimization and performance tuning of key algorithms in cognitive computing fields such as machine learning, deep learning, etc.
2.Lead work in music-related areas such as audio enhancement, content understanding, content generation, multimodal systems, and dialogue systems. Responsible for designing corresponding AI solutions and landing algorithmic model features.
3.Keep abreast of cutting-edge AI technologies, propose innovative methods, and solve business problems in practical music and social application scenarios.
Qualifications:
1.PhD or Master's degree in computer science, mathematics, or related fields. Familiar with fundamental principles of neural networks, recent hot topics such as Attention, Transformer, multimodalities, with experience in development or research in machine learning.
2.Familiar with pre-training models such as BERT series, GPT series, deep learning models like Transformer, and principles/methods of music-related content understanding and content generation. Candidates with experience in combining business requirements are preferred.
3.Experience in practical model development, fine-tuning, and training parameter adjustment. Able to analyze and solve problems encountered during model training.
4.Broad curiosity in various branches of AI technology, good learning ability, and solid development foundation.
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