Binance Accelerator Program - Software Engineer (Backend + AI/LLM)
Binance Hong Kong, Singapore, Taiwan
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Why this grade This listing scored 57/100, which is a C. It lost the most ground on pay transparency. See the breakdown
- Description depth 20 / 20 How much the posting actually says about the work, measured in characters of real text.
- Freshness 12 / 15 How recently it was posted. Older postings are likelier to be filled or abandoned.
- Pay transparency 12 / 25 A published salary range, worth more than any other single factor because it is what a candidate cannot find out without applying.
- Remote clarity 8 / 15 Whether "remote" means anywhere, or is quietly restricted to one country.
- Corroboration 5 / 10 Whether more than one source carries this listing.
- Role specificity 0 / 10 Whether the listing is tagged well enough to tell what the role actually is.
Every figure above is arithmetic over the posting itself — its salary field, its text, its age, its tags and how many sources carry it. How the grades work →
This listing does not state a salary
$125k – $188k
That is the middle half of what comparable roles paid on this board over the last 90 days — 59 listings that did publish a figure, median $160k. It is not this employer's offer, and we have no idea what they pay. It is only what the rest of the market advertised.
About Binance Accelerator Program
Binance Accelerator Program (BAP) is a 3-6 month internship program designed for Early Career talent to have firsthand experience in the rapidly expanding digital assets space. You will be given the opportunity to develop your skills at Binance and understand what it’s like to work at the world's leading blockchain ecosystem. As part of your internship in the BAP, there will also be opportunities for networking and development, which will expand your professional network and build transferable skills to propel you forward in your career. Learn about the BAP Program HERE.Who may apply
Current university students and recent graduates.*Terms of employment / engagement shall be subject to contract and local applicable lawsResponsibility
- Contribute to backend and/or full-stack feature development, testing, and release for core products/platforms, delivering production-ready code.
- Collaborate with senior engineers on module design, API/interface definition, system integration, and deployment (including logging, monitoring, and performance optimization).
- Write and maintain automated tests and CI/CD-related configurations to improve development efficiency and code quality.
- Support the engineering deployment of AI/LLM capabilities based on business needs, such as integrating LLM APIs, building basic RAG pipelines, and embedding tool/agent capabilities into existing systems.
- Help build and maintain datasets and benchmarks for evaluation/regression, track online performance, and assist with debugging and fixing issues.
- Produce necessary technical documentation and communicate effectively across teams.
Requirements
- Currently pursuing a Bachelor’s or Master’s degree in Computer Science, Software Engineering, Artificial Intelligence, or a related field.
- Solid software engineering fundamentals: data structures and algorithms, object-oriented design, common design patterns, and coding best practices.
- Proficient in at least one primary programming language for engineering work; Python is required. Experience with Java/Go/TypeScript/JavaScript is a plus.
- Familiar with common engineering tools and workflows: Git, basic Linux, debugging skills; understanding of unit/integration testing, RESTful APIs, and databases (SQL/NoSQL).
- Some AI/LLM project or internship experience is sufficient (no deep research required), e.g., prompt engineering/function calling, RAG, vector databases, or experience integrating frameworks like LangChain/LangGraph is a plus.
- Strong ownership, good communication and collaboration skills, and the ability to learn quickly and deliver.
- Able to commit to at least 6 months, 5 days per week.
Nice to Have
- Experience shipping web/backend services; knowledge of caching, message queues, concurrency, and performance tuning.
- Familiarity with containerization and deployment (Docker/Kubernetes), cloud platforms (AWS/GCP/Azure), or observability (Prometheus/Grafana/ELK).
- Exposure to LLM evaluation, prompt iteration, data feedback loops, or basic fine-tuning workflows.
Originally posted on Himalayas
Apply for this role Opens himalayas.app — the link as listed; we have not yet verified it is the employer's own page
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Where this listing came from
- 09 Sep 2026 Himalayas first sighting
Seen on 1 board over 0 days.