OKX - Principal AIgorithm Engineer, Search and Recommendation
Upload My Resume
Drop here or click to browse · Tap to choose · PDF, DOCX, DOC, RTF, TXT
Requirements
• Proven end-to-end ownership of production recommendation pipelines at 10M+ DAU scale • 10M+ DAU scale • User Intent & Profiling (Core) — Hands-on experience designing unified intent representations across heterogeneous domains (content / feature / search); demonstrated ability to fuse real-time behavioral signals with long-term stable preferences; experience building tiered user profile systems across the full cold-start → interest exploration → stable preference lifecycle • User Intent & Profiling (Core) • Transformer & Sequential Ranking (Core) — Deep, practitioner-level command of Attention mechanisms in sequential behavior modeling and their production limitations (DIN / SIM / HSTU evolution); ability to propose independent architectural solutions under real engineering constraints; proficiency in Listwise loss functions (ListMLE / Softmax Loss) and joint multi-candidate ranking • Transformer & Sequential Ranking (Core) • Multi-Task Training (Core) — Expert-level knowledge of MMoE / PLE / ESMM architectures; hands-on experience identifying and resolving gradient conflicts; ability to design composite loss function frameworks from scratch; proven methodology for closing the gap between offline metrics (AUC / NDCG) and live business KPIs • Multi-Task Training (Core) • Business Attribution (Core) — Hands-on Uplift Modeling experience; proficiency in Position / Selection Bias correction and prediction probability calibration • Business Attribution (Core) • Familiarity with Semantic Tokenization (FSQ / RQ-VAE), conditional sequence generation, or RLHF / DPO applied to recommendation systems • Engineering experience with LLM Agent frameworks (Tool Use / ReAct) and designing the collaboration boundary between agent-based and traditional recommendation • Hands-on experience with large-scale distributed training (10B+ parameter models), real-time feature pipelines (Flink / Kafka), and inference optimization under strict latency SLAs • Experience in fintech, Web3, or crypto platforms
Responsibilities
• Drive continuous ranking model iteration with measurable, attributable impact on user retention and trading conversion • Build a cross-domain intent framework spanning content consumption, feature usage, and search — shifting the system from tracking what users clicked to understanding what users are trying to do • Chart and execute the technical evolution from Transformer-based sequential ranking toward generative recommendation, including sequence generation and preference alignment • Integrate recommendation and search capabilities into an LLM Agent framework, moving from passive content delivery to proactive intent fulfillment • Mentor senior engineers and help define the broader recommendation research and engineering strategy • What We Look For In You • Master's or above in Computer Science, Mathematics, or a related field from a top university; 8+ years of industry experience with 5+ years in core recommendation or search roles
Benefits
• Competitive total compensation package • L&D programs and Education subsidy for employees' growth and development • Various team building programs and company events • Wellness and meal allowances • Comprehensive healthcare schemes for employees and dependants • More that we love to tell you along the process! • All official OKX vacancies are published on this website. While roles may appear on selected third-party platforms from time to time, information on other sites may be inaccurate or outdated. If in doubt, please apply directly through our official careers website. • If in doubt, please apply directly through our official careers website. • Information collected and processed as part of the recruitment process of any job application you choose to submit is subject to OKX's Candidate Privacy Notice.
No credit card. Takes 10 seconds.