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Shopee

Backend Expert Engineer - Recommendation

4-6 Years

This job is no longer accepting applications

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  • Posted a month ago

Job Description

Job Description:

  • Design, build, and maintain critical backend services for Shopee's recommendation engine, support rapid product and business iteration
  • Optimize the end-to-end recommendation system, including online system, nearline workflows, and offline data pipelines to ensure robustness, scalability, and cost-efficiency
  • Contribute to the abstraction and platformization of reusable recommendation components, driving service modularity and long-term maintainability
  • Research, evaluate, and apply industry best practices and new technologies in recommendation system engineering
  • Collaborate closely with algorithm, product, and platform teams to ensure smooth integration and evolution of the recommendation system.

Requirements:

  • 4+ years of backend engineering experience in recommendation, search, or ads system, with solid understanding of large-scale recommendation system architecture
  • Proficient in Linux-based development environments expertise in C++ or Golang, with strong system-level engineering and design skills.
  • Proven experience designing and optimizing high-concurrency, high-availability backend services
  • Strong problem-solving skills with the ability to abstract complex business logic into scalable system designs
  • Effective cross-functional communication and collaboration skills, with a proactive and ownership-driven mindset
  • Bachelor's degree or above in Computer Science or related field is preferred
  • Experience in leading teams, mentoring peers, or owning core modules in mid-to-large scale systems is a strong plus.

More Info

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About Company

Shopee Pte. Ltd. is a Singaporean multinational technology company that specialises in e-commerce. The company was launched in Singapore in 2015, before it expanded abroad. As of 2021, Shopee is considered the largest e-commerce platform in Southeast Asia with 343 million monthly visitors.

Job ID: 124736857