over 2 years ago
Taipei, Taiwan +2 moreSenior
Responsibilities
- Own production-grade AI data processing pipelines for financial text, tables, layouts, audio, and video, including chunking, deduplication, clustering, standardization, versioning, and validation.
- Build layered financial knowledge bases containing source documents, structured facts, entities, events, full-text indices, vector indices, relationship data, and detailed metadata.
- Engineer and operate production RAG services with query processing, permission and time filtering, multi-route retrieval, reranking, context assembly, evidence citation, and result delivery.
- Design reusable data-processing, knowledge-engineering, and indexing frameworks supporting new sources, formats, languages, models, rules, incremental updates, rebuilds, backfills, deletion, and authorization expiry.
- Integrate LLMs, document understanding models, NLP models, rule systems, and algorithm components with task orchestration, version governance, failure handling, and clear interfaces.
- Build operational capabilities including APIs, asynchronous tasks, queues, caching, retries, graceful degradation, human review, canary releases, rollbacks, fault recovery, and capacity governance.
- Establish quality and observability systems measuring parsing accuracy, retrieval coverage, citation completeness, staleness, latency, stability, and cost.
- Collaborate with data, algorithm, product, and compliance teams to deploy reliable services in equities products and Binance AI.
Requirements
- Master’s degree or above in Computer Science, Software Engineering, AI, or a related field.
- 5+ years of experience in backend, data platforms, ML engineering, or AI application engineering.
- Familiarity with equity markets, investor research workflows, trading mechanics, market data, fundamentals, corporate actions, and major market events.
- Proficiency in Python and at least one of Java or another backend language, with strong software engineering, distributed-systems, and service-interface design skills.
- Production experience with LLM, NLP, or ML systems, including model invocation, orchestration, failure recovery, version governance, and online issue resolution.
- Production experience with knowledge engineering or RAG systems and structured, semi-structured, and unstructured content processing.
- Understanding of full-text search, vector search, document storage, chunking, indexing, filtering, recall, reranking, context assembly, citation, and permission control.
- Experience governing performance, stability, cost, and observability for high-concurrency or large-scale processing systems.
- Experience adapting new data sources or content types and turning source-specific logic into reusable processing capabilities.
Benefits
- Competitive salary and company benefits.
- Work-from-home arrangement; the arrangement may vary depending on the business team’s work.
- Opportunities for career growth and continuous learning.
- Collaboration with world-class talent in a global, user-centric organization.
- Autonomy on unique, fast-paced projects in an innovative environment.
Categories
About Binance
Binance builds a global cryptocurrency exchange and related infrastructure for retail and institutional traders, developers, and businesses. Its products include spot and derivatives trading, fiat on-ramps, wallets, payments, staking, custody, and Web3/NFT services, with revenue driven largely by trading and transaction fees. Founded in 2017 and privately held, it operates worldwide and also stewards the BNB Chain ecosystem, with its main exchange regularly ranking first by crypto trading volume.