Senior Staff Algorithm Engineer, Recommendation
OKX - APAC
Posted Apr 2, 2026
Benefits
- Parental leave
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- Non-birth-parent leave
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- Family-building benefits
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- Fertility benefits: Not verified
- Adoption assistance: Not verified
- Surrogacy assistance: Not verified
- Mental health support
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- Relocation assistance
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- Childcare support
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- Learning budget
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- Salary
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- 401(k) match
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Schedule
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- Weekend work
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Application
- Cover letter
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- Assessment
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- Deadline
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Where they hire
State eligibility is not yet verified.
About this role
Senior Staff Algorithm Engineer, Recommendation APAC 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. About the Role You will own the technical direction of OKX's next-generation social feed recommendation system - evolving it from a content feed into a unified recommendation engine that surfaces both content and platform features. Your decisions directly shape the experience of tens of millions of users and drive platform trading conversion. Responsibilities - Elevate the Ranking System - Drive continuous ranking model iteration with measurable impact on user retention and trading conversion - Unify User Understanding - Build a cross-domain intent framework spanning content consumption, feature usage, and search, shifting the system from "what users clicked" to
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