San Su

Machine Learning Engineer at Nvidia

Based in Los Angeles, United States

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Seniority

Staff

Department

Information Technology

Location

Los Angeles

Industry

Computer Hardware Manufacturing

Company size

45K

Contact information

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Email

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s•••••••@••••••.com

Phone

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Background

About San Su

I am a professional with extensive machine learning engineering experience, currently working at NVIDIA as a senior machine learning engineer. I have a bachelor's degree in computer science and a master's degree in machine learning/English. During my career, I have worked in software development and machine learning related positions at well-known companies such as iFlytek. During my time at iFlytek, I participated in the design, development and testing of software products, as well as the design and implementation of large software projects. At NVIDIA, I worked as a machine learning engineer, responsible for designing, implementing and optimizing machine learning algorithms and models, using NVIDIA's GPU technology to accelerate large-scale data processing and deep learning tasks, and participated in the development and deployment of multiple machine learning projects, promoting the company's technological innovation and product development in the field of artificial intelligence. Currently working at NVIDIA as a senior machine learning engineer, responsible for leading and participating in the design, development and implementation of complex machine learning projects, guiding and training junior engineers, and improving the team's technical level and project management capabilities. At the same time, I participate in the formulation of machine learning technology strategies and R&D plans, promote the company's technological innovation and product development in the field of artificial intelligence, solve the technical challenges of machine learning algorithms and models, optimize model performance and data processing efficiency, and ensure the successful implementation and delivery of projects. Have solid knowledge of machine learning and data science, be proficient in programming languages ​such as Python and C++, as well as machine learning frameworks and tools such as TensorFlow, PyTorch, Caffe, Keras, OpenCV, etc, have relevant skills such as distributed computing, and be able to cope with complex machine learning projects and challenges.

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