LLM Engineer 구성원 영입

D-239/23(수) 23:59 마감3722

경력

채용 유형

정규직

학력

학력무관

지역

경기도 판교

주요 업무

Drive and monitor large-scale LLM training in a multi-GPU environment for a specialized biomedical model Take ownership of the training codebase and pipeline — understanding it in depth, operating it, and extending it as the project evolves Collaborate with external LLM vendors and technology partners to align on training approaches, tools, and workflows Diagnose and resolve training failures, instability, and performance bottlenecks Improve training throughput, memory efficiency, and overall job stability Support model evaluation throughout training, including domain-specific benchmarks relevant to drug discovery and life sciences Maintain well-organized experiments, checkpoints, and technical documentation to ensure reproducibility Collaborate with internal scientific and data teams to prepare training data, configurations, and workflows Establish a reliable, repeatable workflow for future model updates and scaling

자격 요건

Education : Bachelor's degree or higher Major : Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field Experience : 8-18 years of relevant industry experience in machine learning, large language models, or AI systems Hands-on experience training or fine-tuning large language models Strong proficiency in Python and PyTorch Experience with distributed and multi-GPU training Ability to debug effectively using logs, metrics, and experiment outputs Solid understanding of training stability and performance optimization

우대 사항

Experience applying AI or machine learning in biotech, pharmaceutical, or life sciences settings Familiarity with biomedical data, scientific literature, or domain-specific language models Experience with GPU cluster environments or Slurm Experience with LLM serving, inference optimization, or quantization Experience with evaluation frameworks or benchmark testing Experience collaborating with external vendors or technology partners

채용 절차

서류전형 > 필기전형(SKCT) > 면접전형 > 채용검진/처우협의 > 최종합격

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