Job Description
7 days ago
Responsibilities:
1.Responsible for the technical research of large language models related to Bigo's business scenareios including but not limited to pre-training, SFT (Supervised Fine-Tuning), and RLHF (Reinforcement Learning from Human Feedback).
2.Implement large model landing in conjunction with the business scenareios, including data construction, large model evaluation, prompt design, and AI agent development.
3.Keep up with the latest advancements in large model technology, and be responsible for the development and engineering implementation of related technologies, accelerating the landing and optimization of cutting-edge large model technology in business scenarios such as live broadcasting, short video, and instant messaging.
Requirements:
1.Master's or Ph.D. degree in Computer Science, Statistics, Machine Learning, Mathematics, or related fields.
2.Strong engineering implementation ability, proficient in at least one deep learning framework (such as TensorFlow, PyTorch, etc.).
3.Good learning ability, teamwork, and communication skills.
4.Experience in LLM pre-training, SFT, RLHF, Prompt, AI agent, etc. is preferred.
5.Priority will be given to those who have published papers in internationally renowned AI conferences or have won awards in ACM competitions.
1.Responsible for the technical research of large language models related to Bigo's business scenareios including but not limited to pre-training, SFT (Supervised Fine-Tuning), and RLHF (Reinforcement Learning from Human Feedback).
2.Implement large model landing in conjunction with the business scenareios, including data construction, large model evaluation, prompt design, and AI agent development.
3.Keep up with the latest advancements in large model technology, and be responsible for the development and engineering implementation of related technologies, accelerating the landing and optimization of cutting-edge large model technology in business scenarios such as live broadcasting, short video, and instant messaging.
Requirements:
1.Master's or Ph.D. degree in Computer Science, Statistics, Machine Learning, Mathematics, or related fields.
2.Strong engineering implementation ability, proficient in at least one deep learning framework (such as TensorFlow, PyTorch, etc.).
3.Good learning ability, teamwork, and communication skills.
4.Experience in LLM pre-training, SFT, RLHF, Prompt, AI agent, etc. is preferred.
5.Priority will be given to those who have published papers in internationally renowned AI conferences or have won awards in ACM competitions.
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