LLM Recommendation & Agentic AI Engineer

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Binance

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 2017

₿ Crypto

💳 Fintech

💰 Initial Coin Offering on 2020-12

Crypto • Fintech

Binance is the world's leading cryptocurrency exchange, serving over 235 million registered users across more than 180 countries. The platform offers a wide array of services, including the trading of over 350 cryptocurrencies in Spot, Margin, and Futures markets. Users can also buy and sell crypto via Binance P2P, earn interest through Binance Earn, and engage in NFT trading on the Binance NFT marketplace. Binance provides low transaction fees and diverse payment options, making it a preferred choice for cryptocurrency enthusiasts worldwide.

📋 Description

• Design and develop LLM-powered recommendation and personalization systems for financial and Web3 scenarios, including candidate generation, ranking, reranking, user intent understanding, and context-aware recommendation • Explore and build agentic AI systems using internal data, APIs, tools, and domain-specific capabilities for complex financial and trading-related tasks • Develop and optimize tool routing, tool retrieval, planning, and multi-step reasoning mechanisms for large-scale tool ecosystems • Perform post-training of large language models using SFT, preference optimization, reinforcement learning, and other techniques • Build and maintain training and evaluation datasets, benchmarks, and evaluation pipelines for LLM recommendation and agentic systems • Prototype and iterate on LLM and agent workflows, then integrate successful prototypes into production systems • Explore small and specialized language models for routing, recommendation, classification, reranking, and latency-sensitive tasks • Collaborate with senior engineers, researchers, product teams, and domain experts on system design, experimentation, integration, deployment, and continuous optimization

🎯 Requirements

• Current university student or recent graduate • Strong foundation in machine learning, NLP, information retrieval, recommendation systems, or large language models • Hands-on experience in at least one of: large language models and post-training; recommendation systems, ranking, or retrieval; LLM agents and tool-use systems; retrieval-augmented generation; reinforcement learning or preference optimization • Familiarity with SFT, RL, DPO/GRPO-style optimization, prompt engineering, structured generation, function/tool calling, and model evaluation • Understanding of embedding-based retrieval, learning-to-rank, reranking, personalization, user modeling, or generative recommendation • Strong programming skills in Python • Experience with deep learning frameworks such as PyTorch • Ability to conduct experiments independently, analyze model/system performance, and translate research ideas into production solutions • Preferred: experience building production-scale recommendation, search, or LLM systems • Preferred: experience with agent frameworks, tool routing, multi-agent systems, memory systems, or long-horizon agent workflows • Preferred: experience with LLM inference and serving frameworks such as vLLM, SGLang, TensorRT-LLM, or equivalent • Preferred: familiarity with Web3, cryptocurrency, financial markets, or trading systems • Preferred: experience with large-scale datasets, distributed training, model serving, or high-throughput online systems • Publications, open-source contributions, or practical projects related to LLMs, recommendation systems, agents, search, or reinforcement learning are a plus

🏖️ Benefits

• Competitive salary and company benefits • Work-from-home arrangement (the arrangement may vary depending on the work nature of the business team) • Opportunities for networking and development • Opportunities for career growth and continuous learning • Autonomy in an innovative environment • Collaboration with world-class talent in a user-centric global organization with a flat structure