【NLP工程师招聘】_瑞因凡(上海)智能科技有限公司招聘信息-猎聘

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运营总监 · 瑞因凡（上海）智能科技有限公司

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职位介绍: Job Summary: As an ML Engineer specializing in Large Language Models (LLMs), you will play a critical role in designing, implementing, and optimizing the training and inference environment for LLMs. You will work closely with researchers, machine learning and software engineers to ensure scalable and robust LLM infrastructures to advance our capabilities to build and serve best-in-class Foundation Models. Your expertise in building and optimizing LLMs at scale, from data ingestion during training to optimized batch-inference in production, will be key to ensure reliable performance of our model to power the next generation of businesses. Responsibilities: • Collaborate with machine learning operations (MLOps) engineers and ML researchers to scale and optimize LLM training and inference, including data preprocessing & ingestion, distributed training, throughput and inference optimization. • Design and implement scalable data loading strategies and repeatable and resumable model training, validation, and fine-tuning code. • Coordinate, monitor and support training LLMs at scale, including restart and debugging. • Collaborate with software and MLOps engineers to integrate LLMs into production systems. • Implement and enforce best practices for model versioning and training data management. • Participate in code reviews, documentation, and knowledge sharing to promote a collaborative and productive work environment. Qualifications: • 3+ years of working experience in industry, with experience in building robust machine learning models at scale as well as debugging distributed systems. • Proficient in programming languages such as Python, and experience with relevant libraries and frameworks, such as TensorFlow, PyTorch, or similar. • Familiarity with software practices, such as version control (e.g., Git), as well as testing of machine learning models • Strong analytical and problem-solving skills as well as excellent communication and writing in English. Nice to have: • Strong understanding of machine learning principles, algorithms, and frameworks, with expertise in Large Language Models. • Experience with evaluating and testing LLMs • Strong Data Engineering skills for data pre-processing at scale using MapReduce frameworks such as Dask, Spark or Hadoop

其他信息: 语言要求：英语

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