ML Engineer: Scalable Recommender Systems

TikTok

Singapore

On-site

SGD 120,000 - 170,000

Full time

14 days+
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Job summary

TikTok is hiring for an advanced ML/AI role focused on building scalable recommendation systems and ML-powered classifiers. You will work on understanding product goals, user behavior, and content security to enhance the content experience.

The position involves close collaboration with cross-functional teams to expand TikTok’s product reach in important regional markets. Ideal candidates hold a PhD in CS or related, have strong data structures/algorithms foundations, and hands-on programming

Qualifications

  • PhD in CS or related required or nearing completion
  • Solid experience with data structures and algorithms
  • Hands-on coding in a general purpose language
  • Strong communication and teamwork skills
  • Passion for technologies and solving challenging problems
  • Experience in machine learning, recommendation systems, or data mining

Responsibilities

  • Build industry-leading recommendation system; develop scalable classifiers and ML-powered tools
  • Understand product objectives and ML techniques; improve models and recommendations
  • Analyze user behavior; apply ML to optimize content consumption/production
  • Align with content security strategy; apply ML to improve content audit processes
  • Collaborate with cross-functional teams to grow the product in key regional markets

Skills

PhD-related research
Data structures & algorithms
General programming
Communication & teamwork
Tech passion & problem solving
ML/RS/Data mining experience

Education

PhD in computer science or related

Job description

TikTok is hiring for an advanced ML/AI role focused on building scalable recommendation systems and ML-powered classifiers. You will work on understanding product goals, user behavior, and content security to enhance the content experience.

The position involves close collaboration with cross-functional teams to expand TikTok’s product reach in important regional markets. Ideal candidates hold a PhD in CS or related, have strong data structures/algorithms foundations, and hands-on programming

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