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Company Overview
This widely popular mobile application has redefined short-form video content globally. It allows users to create and share brief videos, typically ranging from a few seconds up to 10 minutes, across diverse topics like dance, music, trends, beauty, food, and pets. A key element of its success is a highly sophisticated algorithm that quickly learns user preferences, delivering a uniquely personalized content feed to each individual. The platform also offers features for live interaction and has expanded into e-commerce functionalities.
A leading technology company is seeking a highly skilled and experienced Backend Engineer with a strong focus on Application Computing, specializing in Data and AI. The successful candidate will play a pivotal role in designing, developing, and maintaining the critical backend systems that underpin the company’s large-scale recommendation, search, and advertising platforms.
Responsibilities
Architect and implement highly efficient offline computing systems specifically tailored for large-scale recommendation engines.
Design and develop flexible, scalable, stable, and high-performance storage systems and computing models to support massive data processing.
Proactively identify and resolve issues within production environments, while also designing and implementing robust mechanisms and tools to ensure the overall stability and reliability of these critical systems.
Contribute to the construction of industry-leading streaming computing frameworks and other distributed systems, providing essential and reliable infrastructure for handling massive datasets and large-scale business operations.
Qualifications
Minimum Qualifications
Possession of a Bachelor’s degree or higher in Computer Science or a closely related technical field, coupled with at least 5 years of relevant professional experience.
A deep and demonstrable understanding of big data computing systems, evidenced by hands-on experience with technologies such as Flink, Spark, Paimon, Velox, and other key components within the big data computing stack.
Familiarity with prominent machine learning technology stacks, including core technologies like PyTorch, Large Language Models (LLMs), and multimodal systems, accompanied by practical experience in their application.
Practical experience in developing features and working with data samples within search, advertising, and recommendation systems.
Exceptional coding and troubleshooting abilities, with strong proficiency in programming languages such as Java, C++, Scala, and Python.
Disclaimer
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