Base: $134,900.00 to $253,400.00 py; bonus/equity:...
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Bachelor's degree in computer science or related field
Hands-on experience with large-scale multimodal data
Solid foundation in deep learning algorithms
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Tencent Music Entertainment Group is seeking a Hunyuan Multimodal Algorithm Researcher to contribute to the development of advanced multimodal models, focusing on algorithm design and optimization. The ideal candidate should have a strong background in deep learning and large-scale data processing, alongside excellent communication and teamwork skills.
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Job Summary
The role involves conducting R&D for Omni multimodal large models, covering training data design and model capability evaluation.
Candidates are expected to analyze R&D challenges and devise first-principles solutions to accelerate model iteration and ensure leading-edge performance.
Employees are eligible for a sign-on payment, relocation package, restricted stock units, and comprehensive medical and retirement benefits.
Matching Summary
Match Score: 75
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Tencent Music Entertainment Group is seeking a Hunyuan Multimodal Algorithm Researcher to contribute to the development of advanced multimodal models, focusing on algorithm design and optimization. The ideal candidate should have a strong background in deep learning and large-scale data processing, alongside excellent communication and teamwork skills.
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Salary
Base: $134,900.00 to $253,400.00 per year; Bonus/Equity: Sign-on payment and RSUs available case-by-case; Benefits: Medical, dental, vision, life, disability, 401(k), up to 25 days vacation
Skills & Requirements
Must-have
Bachelor's degree in Computer Science or related field
Hands-on experience with large-scale multimodal data
Solid foundation in deep learning algorithms
Nice-to-have
Publication in top-tier conferences
Experience with Diffusion Models and Autoregressive Models
Participation in ACM or NOI competitions
Key Requirements
Graduate degrees prioritized
Familiarity with cross-modal research preferred
Practical experience in distributed training optimization