Empower User Interaction Scenarios: Align and optimize models for real-world user scenarios, strengthening the model's logical reasoning, instruction following, and detail perception capabilities in multi-turn image-text interactions. Build an online badcase monitoring and data flywheel feedback loop to continuously refine and deliver exceptional interaction experiences.
Who We Look For
Master's degree or above in Computer Science, Software Engineering, Artificial Intelligence, or related fields.
Deep understanding of the Transformer architecture and large language model training principles. Extensive research and hands-on experience in at least one post-training domain, including LLM Alignment, RLHF, Reward Modeling, Personalized LLM, and Memory/RAG mechanisms.
Rich practical experience in user profiling, recommendation systems integrated with large models, or long-context/long-term memory model optimization.
Solid algorithm foundation and engineering implementation skills, proficient in Python, and familiar with deep learning frameworks such as PyTorch and TensorFlow.
Hands-on experience with distributed training, familiar with large-scale training and inference frameworks including Megatron-LM, DeepSpeed, and vLLM.
Experience in training or fine-tuning models at the tens-of-billions to hundreds-of-billions parameter scale.
Excellent research acumen, with publications at top-tier conferences (NeurIPS, ICLR, ICML, ACL, EMNLP, etc.) or significant contributions to high-impact open-source projects (e.g., on HuggingFace).
Strong technical passion and self-drive, adept at analyzing and solving complex problems, with good teamwork and communication skills.
Equal Employment Opportunity at Tencent
As an equal opportunity employer, we firmly believe that diverse voices fuel our innovation and allow us to better serve our users and the community. We foster an environment where every employee of Tencent feels supported and inspired to achieve individual and common goals.
