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Responsibilities
- Engage in the development and optimization of large-scale pre-training language models, including model architecture design, parallel training strategies, and performance improvements
- Drive research and implementation of advanced LLM post-training techniques, including chain-of-thought tuning, preference alignment, and RL for reasoning
- Develop and optimize data collection pipelines for model training, including data de-duplication, cleaning, and verification
- Design and implement solutions for model deployment, including inference optimization and scaling strategies
- Collaborate with cross-functional teams to apply LLM capabilities in various business scenarios, such as materials science
- Stay current with the latest developments in the field and contribute to the company's technical roadmap
- Master's or Ph.D. in Computer Science, AI, or related field
- 5+ years of experience in machine learning, with specific focus on NLP and LLMs
- Strong understanding of transformer architectures and modern LLM frameworks(BERT, GPT, T5)
- Extensive experience with deep learning frameworks (PyTorch, TensorFlow, JAX)
- Strong programming skills in Python and proficiency with ML tools (Hugging Face, DeepSpeed)
- Proven track record in training and optimizing large-scale language models (10B+ parameters) is preferred
- Experience with distributed training systems (Megatron) and optimization techniques is preferred
Key Skills
Ranked by relevance
machine learning
deep learning
tensorflow
pytorch
python
ai
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- Posted
- Dec 18, 2025
- Type
- Full-time
- Level
- Not Applicable
- Location
- Singapore
- Company
- Patsnap
Industries
Software Development
Categories
Engineering
Information Technology
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3 roles aligned with this opportunity
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