[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) # Binance Accelerator Program – Data Scientist (LLM & Trading) Review the role, location requirements, compensation details, and application process before deciding whether this opportunity fits your next career move. [Apply for this job](#job-application)[View company](https://jobicy.com/company/binance.md)ShareRemote from[Singapore](https://jobicy.com/job-region/singapore.md)SalaryUndisclosedDepartment[Data Science & Analytics](https://jobicy.com/categories/data-science.md)EmploymentFull TimeExperienceSeniorPublished29 Oct 2026Apply before28 Nov 2026Listing views37Application actions3Application toolkit ## Make your next move. Prepare your resume, explore your fit, and draft a cover letter for this opportunity. AI Summary ## The role, at a glance. This Binance Accelerator Program role supports the development of AI-powered financial trading agents using Web3 and internal trading data. The candidate will help post-train LLMs with SFT and reinforcement-learning methods, create evaluation datasets, and iterate on financial-agent workflows. The position emphasizes hands-on use of PyTorch or TensorFlow and modern LLM tooling such as Hugging Face Transformers, DeepSpeed, and vLLM. It is suited to a student or early-career practitioner who can commit for at least six months and work closely with senior engineers. The environment is global, fast-paced, and requires strong learning agility and communication. ## Role DNA A quick view of the complexity, pace, ownership and collaboration implied by the job description. ### Job Complexity 4/5EasyHard ### Pace & Pressure 5/5RelaxedFast-paced ### Autonomy Level 3/5GuidedFull ownership ### Communication Load 4/5IndependentCollaborative AI insightThe role requires specialized practical knowledge of LLM post-training, reinforcement learning, model evaluation, and financial-agent systems. Although it is an accelerator role with senior-engineer support, the technical stack and fast delivery expectations make it demanding. ## Salary analysis Estimated compensation compared with the broader US market for similar roles. Estimated job median (per month)Market rate$3,000US market range (per month)$2k–$4.50k0$4.95k AI insightThe monthly pay period is inferred from the job context; it was not explicitly stated by the employer. No employer pay range is disclosed. The displayed figures are AI-estimated monthly USD compensation for a full-time, early-career LLM/data-science accelerator role and are not verified Binance compensation. ## Core skills Skills and capabilities most closely associated with this opportunity. [Large Language Models](https://jobicy.com/jobs?search_keywords=Large%20Language%20Models.md)[Supervised Fine-Tuning](https://jobicy.com/jobs?search_keywords=Supervised%20Fine-Tuning.md)[Reinforcement Learning](https://jobicy.com/jobs?search_keywords=Reinforcement%20Learning.md)[RLHF](https://jobicy.com/jobs?search_keywords=RLHF.md)[RLAIF](https://jobicy.com/jobs?search_keywords=RLAIF.md)[PyTorch](https://jobicy.com/jobs?search_keywords=PyTorch.md)[TensorFlow](https://jobicy.com/jobs?search_keywords=TensorFlow.md)[Hugging Face Transformers](https://jobicy.com/jobs?search_keywords=Hugging%20Face%20Transformers.md)[DeepSpeed](https://jobicy.com/jobs?search_keywords=DeepSpeed.md)[vLLM](https://jobicy.com/jobs?search_keywords=vLLM.md)[LLM Evaluation](https://jobicy.com/jobs?search_keywords=LLM%20Evaluation.md)[Benchmark Dataset Development](https://jobicy.com/jobs?search_keywords=Benchmark%20Dataset%20Development.md)[AI Agents](https://jobicy.com/jobs?search_keywords=AI%20Agents.md)[Web3 Data](https://jobicy.com/jobs?search_keywords=Web3%20Data.md)[Financial Trading Systems](https://jobicy.com/jobs?search_keywords=Financial%20Trading%20Systems.md) Sample interview questionsHow would you evaluate whether supervised fine-tuning improved a trading-focused LLM?I would define task-specific benchmarks covering tool selection, market-data interpretation, structured output accuracy, and safety constraints. I would compare the base and fine-tuned models using automated metrics, error analysis, and controlled human review, while ensuring the evaluation data is separate from training data. What is the difference between SFT and RLHF/RLAIF in LLM post-training? SFT teaches the model to imitate high-quality demonstrations, making it effective for establishing desired formats and baseline behavior. RLHF and RLAIF optimize model behavior against preference signals from humans or AI feedback, which can improve helpfulness, tool use, and adherence to more nuanced objectives. How would you build a benchmark dataset for a financial AI agent? I would first define representative user tasks and failure modes, then collect or create examples with clear ground truth, tool-call expectations, and safety labels. I would version the dataset, separate development and held-out test sets, balance task categories, and regularly review examples for data leakage and changing market assumptions. Which considerations are important when using Web3 data for trading-agent development? I would validate data provenance, timestamps, chain coverage, and handling of forks or missing records. I would also avoid look-ahead bias, preserve reproducibility through versioned data pipelines, and ensure that agent outputs are bounded by risk controls rather than treated as unreviewed trading advice. Describe how you would troubleshoot unstable reinforcement-learning training for an LLM. I would inspect reward distributions, KL divergence, policy loss, value loss, gradient norms, and response quality across checkpoints. I would then test smaller learning rates, reward normalization, clipping settings, batch composition, and data quality, while comparing results against an SFT-only baseline to isolate the cause. Opportunity details ## About this role. 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. 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) Responsibilities: Leveraging knowledge of large-scale models and intelligent agents, participate in the design and development of a series of AI-powered financial trading agency skills based on Web3 data, and integrate them into practical systems. Perform post-training of large-scale language models (SFT, RL, etc.) to enhance the model’s ability to utilize Binance’s internal trading skills. Assist in building and maintaining benchmark datasets to evaluate the performance of AI systems, and assist in building and iterating workflow prototypes for financial AI agent systems. Work closely with senior engineers to complete system design, integration, and deployment. Requirements: Currently pursuing or holding a Bachelor’s, Master’s, or Ph.D. degree in Computer Science, Artificial Intelligence, Financial Engineering, Automation, or a related field. Hands-on experience with post-training techniques such as Supervised Fine-Tuning (SFT) and Reinforcement Learning (RLHF / RLAIF) . Familiar with common fine-tuning and reinforcement learning frameworks, such as Llama Factory, Slime, Verl, and OpenRLHF. Familiarity with at least one mainstream deep learning framework (PyTorch, TensorFlow) and common LLM training/evaluation toolkits (Hugging Face Transformers, DeepSpeed, vLLM, etc.). Excellent communication skills and a strong willingness to learn quickly. Able to commit at least 6 months, working 5 days a week. Why choose Binance? • Shape the future with the world’s leading blockchain ecosystem • Work alongside world-class talent in a user-centric, flat, global organization • Independently complete unique and fast-paced projects in an innovative environment • Thrive in a results-oriented work environment with opportunities for career development and continuous learning • Competitive compensation and benefits、 • Work-from-home available (specific arrangements may vary depending on the nature of the business team) Good communication skills and willingness to learn quickly. Ability to commit at least for a 6 months tenure, 5 days per week. 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. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. 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. 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/157697-binance-accelerator-program-data-scientist-llm-trading.md) > Annual salary information is not provided for this position. 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