Senior Recommendation System Engineer

Responsibilities

• Develop and refactor high-concurrency, low-latency recommendation serving engines including multi-channel recall, coarse ranking, fine ranking, and re-ranking
• Implement dynamic compute trimming and degradation mechanisms for UI personalization and strategy dispatch
• Build high-throughput real-time feature streams using Kafka and Flink
• Contribute to unified online/offline feature storage and govern feature consistency
• Construct and optimize large-scale vector retrieval systems using Faiss, Milvus, or NSW
• Manage high-performance online deployment and operator optimization for deep ranking models like DIN, SIM, MMoE, and PLE
• Ensure global service availability (>99.9%) and P99 latency targets
• Build and maintain distributed tracing and monitoring systems using Jaeger and Prometheus
• Upgrade A/B experimentation platforms including variance reduction and sequential testing mechanisms

Requirements

• 5+ years of recommendation system engineering experience at consumer-scale internet companies
• Proven experience building recommendation systems from 0 to 1
• Proficiency in Go, Java, or C++ (Go preferred)
• Experience with PyTorch or TensorFlow for model online inference and deployment
• Hands-on experience with Spark, Flink, and Kafka stacks
• Proficiency in Milvus or Faiss cluster deployment and tuning
• Deep understanding of collaborative filtering, two-tower recall, and multi-objective optimization
• Strong system design capability in recommendation, feature, or experimentation platforms

About the Company

Established in 2018, Bybit is one of the world’s leading cryptocurrency exchanges and digital financial platforms, serving over 80 million users across more than 200 countries and regions.