Distributed Training & Inference Optimization Engineer (LLM) - GPU Optimization Department (GPUOD)

Role summary

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The Distributed Training & Inference Optimization Engineer at Rakuten is responsible for optimizing large language models (LLM) and GPU performance. Candidates should have expertise in distributed systems, machine learning, and GPU programming. Proficiency in Python, CUDA, and deep learning frameworks like TensorFlow or PyTorch is essential. The role demands strong problem-solving skills and the ability to work collaboratively in a fast-paced environment.

About the employer

Rakuten is a leading global innovation company headquartered in Japan, known for its diverse range of services including e-commerce, fintech, digital content, and communications. With a mission to empower people and society through innovation, Rakuten has a strong presence in over 29 countries and regions, providing a wide array of services to millions of users worldwide. The company fosters a dynamic and inclusive work environment, encouraging creativity and collaboration among its employees.