Senior/ Machine Learning Engineer (LLM)

Singapore

PatSnap

Patsnap empowers IP and R&D teams with advanced AI to get better answers and make faster decisions. Increase IP productivity by 75% while reducing R&D wastage by 25%.

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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.

Qualifications

  • 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.
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* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰

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Tags: Architecture BERT Computer Science Deep Learning GPT JAX LLMs Machine Learning Model deployment Model training NLP Pipelines Python PyTorch Research TensorFlow

Region: Asia/Pacific
Country: Singapore

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