[All remote jobs](https://jobicy.com/jobs.md)[![Binance logo](https://jobicy.com/data/server-nyc0409/galaxy/mercury/2025/06/bc822f38-221.jpg)](https://jobicy.com/company/binance.md)[Binance](https://jobicy.com/company/binance.md) # LLM Applied Data Scientist (RAG/ NLP) AI Summary Binance seeks an applied data scientist/research engineer to build and improve production RAG, retrieval, ranking, and multimodal AI systems. The role covers vector search, embeddings, reranking, context engineering, query rewriting, and evaluation of advanced retrieval approaches such as GraphRAG. The successful candidate will contribute to LLM training workflows including pre-training, supervised fine-tuning, and reinforcement learning, while integrating scalable pipelines with infrastructure and application teams. Strong Python or C++ and PyTorch expertise, deep information-retrieval knowledge, and the ability to take research from design through deployment are central to the position.[Apply for this job](#job-application)[View company](https://jobicy.com/company/binance.md)ShareRemote from[Singapore](https://jobicy.com/job-region/singapore.md), [Hong Kong](https://jobicy.com/job-region/hong-kong.md)SalaryUndisclosedDepartment[Data Science & Analytics](https://jobicy.com/categories/data-science.md)EmploymentFull TimeExperienceOpen levelPublished9 Nov 2026Apply before9 Dec 2026Listing views43Application actions4Application toolkit ## Make your next move. Prepare your resume, explore your fit, and draft a cover letter for this opportunity. Opportunity details ## About this role. [Binance](https://jobicy.com/company/binance.md) 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](https://www.binance.com/en/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. Show more [Apply now >](https://jobicy.com/jobs/160069-llm-applied-data-scientist-rag-nlp.md) > Annual salary information is not provided for this position. Explore salary ranges for similar roles in our [Salary Directory ›](https://jobicy.com/salaries.md) * ![Upload CV](data:image/svg+xml;base64,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) ### Upload your resume now To unlock remote work opportunities and be discovered by global employers. This job listing has been manually reviewed by the Jobicy Trust & Safety Team for compliance with our posting guidelines, including verification of the company's legitimacy, accuracy of job details, clarity of remote work policy, and absence of misleading or fraudulent content. ## Role DNA A quick view of the complexity, pace, ownership and collaboration implied by the job description. ### Job Complexity 5/5EasyHard ### Pace & Pressure 5/5RelaxedFast-paced ### Autonomy Level 5/5GuidedFull ownership ### Communication Load 4/5IndependentCollaborative AI insightThis is a senior, research-intensive applied AI role requiring both theoretical depth in LLMs and information retrieval and the engineering ability to deploy scalable systems. The scope spans model training, advanced retrieval research, evaluation, and cross-functional production integration. ## Salary analysis Estimated compensation compared with the broader US market for similar roles. Estimated job median (per year)Market rate$165,000US market range (per year)$135k–$210k0$231.00k AI insightThe yearly pay period is inferred from the job context; it was not explicitly stated by the employer. No employer pay range is disclosed. The yearly cadence is inferred from the apparent full-time senior applied AI role; the displayed USD figures are estimated annual market compensation, not employer-confirmed pay. ## Core skills Skills and capabilities most closely associated with this opportunity. [Python](https://jobicy.com/jobs?search_keywords=Python.md)[PyTorch](https://jobicy.com/jobs?search_keywords=PyTorch.md)[Natural Language Processing](https://jobicy.com/jobs?search_keywords=Natural%20Language%20Processing.md)[Retrieval-Augmented Generation](https://jobicy.com/jobs?search_keywords=Retrieval-Augmented%20Generation.md)[Information Retrieval](https://jobicy.com/jobs?search_keywords=Information%20Retrieval.md)[Vector Databases](https://jobicy.com/jobs?search_keywords=Vector%20Databases.md)[Embedding Models](https://jobicy.com/jobs?search_keywords=Embedding%20Models.md)[Reranking](https://jobicy.com/jobs?search_keywords=Reranking.md)[Query Rewriting](https://jobicy.com/jobs?search_keywords=Query%20Rewriting.md)[Large Language Models](https://jobicy.com/jobs?search_keywords=Large%20Language%20Models.md)[Reinforcement Learning](https://jobicy.com/jobs?search_keywords=Reinforcement%20Learning.md)[Multimodal Learning](https://jobicy.com/jobs?search_keywords=Multimodal%20Learning.md)[GraphRAG](https://jobicy.com/jobs?search_keywords=GraphRAG.md)[Machine Learning Engineering](https://jobicy.com/jobs?search_keywords=Machine%20Learning%20Engineering.md) Sample interview questionsHow would you design a production RAG pipeline for a large and frequently changing knowledge base?I would separate ingestion, chunking, embedding, indexing, retrieval, reranking, context construction, and generation into observable components. I would use incremental indexing, metadata filtering, hybrid retrieval where appropriate, a reranker for precision, and offline plus online evaluation to track answer quality, latency, and retrieval recall. What metrics would you use to evaluate retrieval quality and end-to-end RAG performance? For retrieval, I would measure Recall@K, MRR, nDCG, and coverage against curated relevance judgments. For end-to-end performance, I would evaluate groundedness, answer correctness, citation accuracy, task completion, latency, and failure rates, supplemented by human review for high-impact use cases. Describe how you would improve a retriever when relevant documents are not appearing in the top results. I would first diagnose whether the issue comes from corpus quality, chunking, embeddings, query formulation, indexing, or ranking. Potential improvements include domain fine-tuning embedding models, query rewriting or expansion, hybrid lexical-semantic retrieval, metadata-aware filtering, hard-negative training, and cross-encoder reranking. How have you moved a machine-learning research idea into a reliable production service? I begin with a measurable hypothesis and reproducible offline benchmark, then build a modular implementation with versioned data and model artifacts. Before release, I validate latency, reliability, safety, and cost under realistic load, deploy behind monitoring and experiment controls, and iterate using production feedback. How would you decide whether GraphRAG is more appropriate than standard vector retrieval? I would choose GraphRAG when questions require multi-hop reasoning across explicit entities and relationships, where isolated document similarity loses important structure. I would compare it against strong vector and hybrid baselines on representative tasks, considering answer quality, freshness, graph-maintenance cost, and latency before adopting it. Next step ## Apply now. Follow the employer’s application method and review Jobicy’s safety guidance before sharing personal information. Keep exploring ## Related remote jobs. * ![Teamworks logo](https://jobicy.com/data/server-nyc0409/galaxy/mercury/2026/11/de7f1534a7c5-221.webp) Teamworks Nov 9 New ### [Data Scientist II (Soccer)](https://jobicy.com/jobs/160270-data-scientist-ii-soccer.md) We’re hiring a Data Scientist II on our Soccer team to develop the statistical and machine learning models our partner clubs use for player recruitment. 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