AI Senior / Lead Engineer (Recommendation)

Who we are

At OKX, we believe that the future will be reshaped by crypto, and ultimately contribute to every individual's freedom.

OKX is a leading crypto exchange, and the developer of OKX Wallet, giving millions access to crypto trading and decentralized crypto applications (dApps). OKX is also a trusted brand by hundreds of large institutions seeking access to crypto markets. We are safe and reliable, backed by our Proof of Reserves.

Across our multiple offices globally, we are united by our core principles : We Before Me, Do the Right Thing, and Get Things Done. These shared values drive our culture, shape our processes, and foster a friendly, rewarding, and diverse environment for every OK-er.

OKX is part of OKG, a group that brings the value of Blockchain to users around the world, through our leading products OKX, OKX Wallet, OKLink and more.

The  Rmendation Team  plays a crucial role in optimizing user experiences by delivering relevant and engaging content in real-time. We develop and refine machine learning algorithms that power  content feeds, personalized rmendations, and user growth strategies.  Our work directly impacts user satisfaction and engagement on the OKX platform, helping drive business growth and content quality. We are looking for engineers who are passionate about rmendation systems, machine learning, and large-scale AI applications.

What You'll Do :

• Develop and optimize large-scale rmendation algorithms  to improve personalized user experiences in content feeds, rmendations, and engagement-driven interactions.
• Implement and enhance retrieval, ranking, and re-ranking models  to refine rmendation precision and diversity.
• Apply sequence-based models  (, Transformers, RNNs) to understand  user behavior over time  and improve personalization.
• Improve recall mechanisms  using collaborative filtering, content-based filtering, and deep learning-based vector search techniques.
• Leverage multi-modal learning  (text, image, graph) to enhance content understanding and personalization.
• Collaborate cross-functionally  with product managers, data engineers, and infrastructure engineers to refine rmendation strategies.
• Run A / B tests  to assess the performance of rmendation algorithms, analyze results, and iterate accordingly.
• Enhance system efficiency and scalability , ensuring high-performance model deployment in real-world production environments.
• Stay updated with the latest research  in rmendation systems, machine learning, and AI to integrate cutting-edge innovations into production systems.

Qualifications :

Preferred Qualifications :

Perks & Benefits