Intelligent Video Architect

2 weeks ago

Singapore beBeeMachineLearning Full time $120,000 - $150,000

About Us

We are a leading short-form mobile video platform, driven by creativity and joy.

We strive to achieve great things with talented individuals. We lead with curiosity, humility, and a desire to make an impact in the tech industry. Every challenge is an opportunity to learn and innovate as one team.

Responsibilities:

  • We use algorithms to identify and predict risks and low-quality merchants, products, and creators in e-commerce scenarios, and assist businesses in managing and controlling them.
  • We use algorithms to identify events and behaviors that affect product experience and efficiency, and build data models to help create a favorable ecosystem and support business operations.
  • We participate in building data for various entities such as e-commerce live streaming/video, products, merchants, and creators, building large-scale network/feature sequence models to support business scenarios such as content understanding, multimodal representation, community mining, and solving problems related to products, live streaming, and video management, and providing support for them.
  • We participate in building a large-scale graph storage and graph learning platform to improve relationship building and governance within our e-commerce community.
  • We explore and research cutting-edge technologies in machine learning/graph learning/sequence learning and related fields, implementing these technologies in practical business scenarios, and supporting the production of scalable and optimized machine learning models.

Required Skills and Qualifications:

Minimum Qualifications:

  • A final year PhD graduate in Computer Science, engineering or quantitative field.
  • Solid coding skills, familiar with deep learning/graph neural network/machine learning frameworks such as PyTorch, TensorFlow, DGL, pyg, sklearn, etc.
  • Familiar with one or more algorithms in machine learning/graph learning/sequence learning, such as graph modeling, timing signal modeling, node/subgraph classification, community mining, representation learning, self-supervised/semi-supervised learning, with a certain depth and breadth.
  • Relevant industry experience with a solid theoretical foundation of machine learning.

Preferred Qualifications:

  • Good teamwork and communication skills, practical experience in relevant business scenarios is preferred.
  • Published papers in high-level computer science conferences (ACL, EMNLP, NIPS, AAAI, etc.) or have competition experience are preferred.
  • Familiar with the application of related algorithms in data mining, search recommendation, content understanding, and governance risk control preferred.
  • Skilled in numpy and pandas for modeling experiments, familiar with big data tools such as Hive, Spark, Hadoop preferred.

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