LLM Applied Data Scientist (RAG/ NLP)

Binance
Hong Kong +1 more
On-site

Who this role is best for

Strong fit for data scientists with expertise in RAG and NLP who can translate research into scalable systems, working in a global, remote-first environment with a focus on blockchain and cryptocurrency.

Best fit for

  • Candidates with RAG and NLP research experience and a track record of deploying AI systems in production
    — “translate research into scalable, production-level systems”
  • Professionals with a background in information retrieval and deep learning, especially in embeddings and reranking
    — “solid theoretical foundation in information retrieval, NLP, and deep learning (experience with embeddings, reranking, query understanding preferred)”

Things to consider

  • Work arrangement flexibility may vary depending on the team and role specifics
    — “Work-from-home arrangement (the arrangement may vary depending on the work nature of the business team)”
  • Candidates must be prepared to work in a fast-paced, innovative environment with high autonomy
    — “Tackle unique, fast-paced projects with autonomy in an innovative environment”

How to stand out

  • Emphasize experience with multimodal and graph-based retrieval methods in your resume and interviews
    — “Research and evaluate advanced AI-native retrieval algorithms (e.g., low-latency, multimodal retrieval, hierarchical retrieval, GraphRAG)”
  • Highlight your ability to design and implement robust evaluation methodologies for AI systems
    — “design and implement robust evaluation methodologies”
  • Showcase projects where you optimized retrieval and ranking pipelines for user experience improvements
    — “Develop and optimize retrieval and ranking pipelines (indexing, vector search, retrieval scoring, reranking) to improve user experience”
  • Demonstrate your ability to solve complex tasks using System 2 thinking and advanced decoding strategies
    — “solve complex tasks using System 2 thinking and applying advanced decoding strategies such as MCTS and A*”
  • Include experience with integrating RAG pipelines into production systems as a key differentiator
    — “Collaborate with infrastructure and application teams to integrate RAG pipelines into production systems”
Pace · SteadyCollaboration · HighAutonomy · MediumDecision Impact · Company

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • improved model performance
  • robust evaluation methodologies
Typical background
research scientistmachine learning engineer

Skills & requirements

Required

Data ProcessingReinforcement LearningNLPCVMultimodal Methods

Preferred

LLMRAG

Stack & domain

Data ProcessingRetrieval PipelinesAi-native Retrieval AlgorithmsLLM TrainingNLPCVMultimodal MethodsUser-generated Content AnalysisResearchEvaluationCollaborationInnovationGrowthRisk AwarenessCross-cultural CommunicationBlockchainCryptocurrencyAIMachine Learning

About the role

Original posting from Binance via Greenhouse

Binance is a leading global blockchain ecosystem behind the world’s largest cryptocurrency exchange by trading volume and registered users. We are trusted by 300+ million people in 100+ countries for our industry-leading security, user fund transparency, trading engine speed, deep liquidity, and an unmatched portfolio of digital-asset products. Binance offerings range from trading and finance to education, research, payments, institutional services, and more. Our mission is to increase the freedom of money and financial access for people around the world.

About the Role

We are seeking a highly skilled Research Scientist/Engineer to advance the reasoning and planning capabilities of large foundation models. In this role, you will enhance model performance across the entire development lifecycle—including data acquisition, supervised fine-tuning (SFT), reward modelling, and reinforcement learning—while driving innovations in reasoning and decision-making. You will synthesise large-scale, high-quality datasets through rewriting, augmentation, and generation techniques to strengthen foundation models during pretraining, SFT, and RL stages. A key part of the role involves solving complex tasks using System 2 thinking and applying advanced decoding strategies such as MCTS and A*. You will design and implement robust evaluation methodologies, teach models to interact with external tools, APIs, and code interpreters, and build agents and multi-agent systems capable of addressing sophisticated real-world problems.

Why Binance

  • Shape the future with the world’s leading blockchain ecosystem
  • Collaborate with world-class talent in a user-centric global organization with a flat structure
  • Tackle unique, fast-paced projects with autonomy in an innovative environment
  • Thrive in a results-driven workplace with opportunities for career growth and continuous learning
  • Competitive salary and company benefits
  • Work-from-home arrangement (the arrangement may vary depending on the work nature of the business team)

Binance is committed to being an equal opportunity employer. We believe that having a diverse workforce is fundamental to our success.

By submitting a job application, you confirm that you have read and agree to our Candidate Privacy Notice.

Responsibilities

Design, develop, and optimize data processing and retrieval pipelines for enterprise-level generative tasks and mode training applications   (Customer Service, Token Report, Web3 Domain Models). This includes embedding, reranking, context engineering, and query rewriting models.

Research and evaluate advanced AI-native retrieval algorithms (e.g., low-latency, multimodal retrieval, hierarchical retrieval, GraphRAG) to strengthen large-scale LLM/VLM/Agentic AI capabilities in Binance products.

Collaborate with infrastructure and application teams to integrate RAG pipelines into production systems, ensuring scalability, reliability, and measurable business impact.

Develop and optimize retrieval and ranking pipelines (indexing, vector search, retrieval scoring, reranking) to improve user experience.

Participate in LLM training and RAG system, staying current with techniques such as pre-training, SFT, and reinforcement learning, and apply them to retrieval and generation tasks.

Apply NLP, CV, and multimodal methods to analyze user-generated content (classification, quality evaluation, trend detection, comment analysis).

Requirement

Master’s in Information Retrieval, NLP, Machine Learning, Computer Vision, Multimodal Learning, or related fields.

Proficient in PyTorch with strong coding skills in Python or C++.

Strong communication skills, intellectual curiosity, and passion for lifelong learning. Able to identify opportunities and drive cutting-edge retrieval & RAG technologies into real-world applications.

Solid theoretical foundation in information retrieval, NLP, and deep learning (experience with embeddings, reranking, query understanding preferred).

Hands-on experience with RAG, vector databases, multimodal/graph retrieval, or large-scale AI systems.

Strong engineering ability to translate research into scalable, production-level systems.

Self-driven, able to own projects end-to-end (design → implementation → deployment).

Publications in top-tier conferences/journals (NeurIPS, ICML, ACL, CVPR, SIGIR, KDD, WWW) are a plus; awards in ACM/ICPC or similar competitions preferred.

Why Binance

Shape the future of finance 

Collaborate with world-class talent in a user-centric global organization with a flat structure

Tackle challenging projects in a fast-paced and innovative enviornment with autonomy

Thrive in a results-driven workplace with opportunities for career growth and continuous learning

Competitive salary and company benefits

Remote-first, work-from-home arrangement (may vary depending on the nature of the role and team)

Binance is committed to being an equal opportunity employer. We believe that having a diverse workforce is fundamental to our success.

By submitting a job application, you acknowledge that you have read our Candidate Privacy Notice.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

Source: Binance careers (Greenhouse)

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