Senior Staff Algorithm Engineer, Recommendation
Quick Summary
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…
Background — Master's or above in CS / Math from a top university; 8+ years of experience with 5+ years in core recommendation / search roles; track record of owning end-to-end recommendation pipelines at 10M+ DAU scale User Intent & Profiling…
About the Role
~1 min readResponsibilities
~1 min read- →
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 "what users are trying to do"
- →
Define the Technical Roadmap — Chart and execute a 12–24 month evolution from Transformer-based ranking toward generative recommendation (sequence generation + preference alignment)
- →
Pioneer the Agent Paradigm — Integrate recommendation and search capabilities into an LLM Agent framework, enabling proactive intent fulfillment rather than passive content delivery
Requirements
~2 min read-
Background — Master's or above in CS / Math from a top university; 8+ years of experience with 5+ years in core recommendation / search roles; track record of owning end-to-end recommendation pipelines at 10M+ DAU scale
-
User Intent & Profiling (Core) — Experience designing unified intent representations across heterogeneous domains (content / feature / search); ability to fuse real-time behavioral signals with long-term stable preferences; hands-on experience with tiered user profile systems (cold-start → interest exploration → stable preference)
-
Transformer & Ranking (Core) — Deep understanding of Attention mechanisms in sequential behavior modeling and their limitations (DIN / SIM / HSTU evolution); ability to propose independent solutions under engineering constraints; proficiency in Listwise losses (ListMLE / Softmax Loss) and joint multi-candidate ranking
-
Multi-Task Training (Core) — Expert-level knowledge of MMoE / PLE / ESMM and gradient conflict identification and mitigation; ability to design composite loss function frameworks from scratch; proven methodology for bridging offline metrics (AUC / NDCG) and online business KPIs
-
Business Attribution (Core) — Hands-on Uplift Modeling experience; proficiency in Position / Selection Bias correction and prediction probability Calibration
-
Generative Recommendation (Strong Plus) — Understanding of Semantic Tokenization (FSQ / RQ-VAE) and conditional sequence generation; working-level knowledge of RLHF / DPO applied to recommendation systems
-
Recommendation & Search Agent (Strong Plus) — Engineering experience with LLM Agent frameworks (Tool Use / ReAct); ability to define the collaboration boundary between Agent-based and traditional recommendation; experience designing systems that translate natural language intent into structured retrieval requests
-
Engineering — Large-scale distributed training (10B+ parameter models); real-time feature engineering (Flink / Kafka); inference optimization under strict latency SLA
Nice to Have
~1 min readWhat We Offer
~1 min readLocation & Eligibility
Listing Details
- Posted
- April 2, 2026
- First seen
- April 2, 2026
- Last seen
- May 19, 2026
Posting Health
- Days active
- 46
- Repost count
- 0
- Trust Level
- 38%
- Scored at
- May 19, 2026
Signal breakdown

OKX is a global cryptocurrency exchange and Web3 technology company, offering trading, wallet services, and access to decentralized finance. Founded in 2017, it serves millions of users in over 100 countries.
View company profilePlease let Okx know you found this job on Jobera.
Similar Algorithm Engineer jobs
View all →Browse Similar Jobs
Stay ahead of the market
Get the latest job openings, salary trends, and hiring insights delivered to your inbox every week.
No spam. Unsubscribe at any time.