Senior Machine Learning Platform Engineer

1 week ago

Singapore Shopee Full time

DepartmentEngineering and Technology- LevelExperienced (Individual Contributor)- LocationSingaporeThe Engineering and Technology team is at the core of the Shopee platform development. The team is made up of a group of passionate engineers from all over the world, striving to build the best systems with the most suitable technologies. Our engineers do not merely solve problems at hand; We build foundations for a long-lasting future. We don't limit ourselves on what we can or can't do; we take matters into our own hands even if it means drilling down to the bottom layer of the computing platform. Shopee's hyper-growing business scale has transformed the most "innocent" problems into huge technical challenges, and there is no better place to experience it first-hand if you love technologies as much as we do. Browse our Engineering and Technology team openings to see how you can make an impact with us.

**About the Team**:

- Shopee Paid ads team was established in 2016 to provide an e-commerce advertising platform by relying on Shopee’s massive data. Our expertise covers data, high performance AI-based online services, distributed systems, machine learning algorithms, and ads business strategies. The team places a strong emphasis on technology and strives to achieve innovation.- Involved in the design, development and maintenance of model management and deployment platform for advertising
- Design and implement high-available, high-performance, scalable systems that can support large amount of data
- Design, develop and maintain the infrastructures for advertising machine learning platforms

**Requirements**:

- Bachelor’s degree or higher in Computer Science or relevant fields with solid understanding of network, operating system (Linux), data structure and algorithm.
- Be interested in system development and optimisation.
- Familiar with Python and c/c++.
- Experience in CUDA programming and RDMA is a plus.
- Familiar with TensorFlow, PyTorch, or MXNe, and deep learning fundamentals.
- Experience in GPU training acceleration is a plus.
- Understanding of the principles and implementation methods for data parallelism and model parallelism and experience in optimisation on Horovod or Parameter Server is a plus.
- Rich experience in implementation and optimisation on large-scale distributed systems, or publication records of system research on conferences/journals is a plus.

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