Pioneer Talent Program - Applied Data Scientist

Binance; United States; Remote; USD 120,000 - 190,000; Full time

Benefits offered by this job

Remote‑first company culture

Competitive compensation

Global, diverse team

Job summary

Binance is seeking an Applied Data Scientist to join the Algorithm team. You will design, build, and improve AI agents that understand markets and reason over on‑chain data for hundreds of millions of users.

You will work on chain‑level reasoning, multi‑agent orchestration, and production deployment in a fast‑paced trading environment. You will develop for real environments, focusing on latency, reliability, and scalable test‑time improvements, leveraging frameworks like vLLM and TensorRT‑LLM

Qualifications

• Strong Python programming and AI engineering background.
• Experience with LLMs, prompt engineering, and production pipelines.
• Familiarity with multi-agent system design and tool use.

Responsibilities

• Design and implement production‑grade LLM pipelines powering Binance AI products.
• Improve agent capabilities regarding understanding, reasoning, and action execution.
• Build evaluation frameworks for reasoning model outputs in crypto contexts.

Skills

Python programming

LLM systems

Multi-agent systems

Prompt engineering

AI engineering

Education

Bachelor’s or Master’s degree in CS/EE/Statistics

Tools

vLLM

TensorRT-LLM

Python tooling

Job description

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 an Applied Data Scientist to join our Algorithm team — a hands‑on builder at the intersection of LLM systems, agentic AI, and crypto‑native intelligence.

You will design, build, and improve AI agents that understand markets, reason over on‑chain data, and take actions at speed for hundreds of millions of users — across reasoning models that plan before they act, multi‑agent systems that orchestrate complex crypto workflows, and test‑time scaling that pushes inference‑time intelligence to its limits.

You build for real environments: designing agent architectures, improving performance across quality and latency, developing evaluation methods for open‑ended tasks, and turning research ideas into production.

Responsibilities

• Design and implement production‑grade LLM pipelines powering Binance AI Products and next‑generation agentic trading features — including multi‑step reasoning agents, tool‑selection frameworks, and autonomous workflow execution across spot, perpetual, and on‑chain markets
• Continuously improve agent capabilities in understanding, reasoning, tool selection, and action execution — optimizing simultaneously for intelligence, latency, and reliability under high‑frequency trading constraints
• Build and maintain evaluation frameworks for reasoning model outputs in crypto contexts — covering market analysis accuracy, agent decision quality, hallucination detection, and adversarial robustness against prompt injection in financial workflows
• Apply test‑time scaling techniques — chain‑of‑thought, self‑consistency, process reward models — to push agent reasoning quality in ambiguous, fast‑moving market conditions
• Architect AI system components with rigorous attention to inference latency, throughput, and cost efficiency — leveraging serving frameworks such as vLLM and TensorRT‑LLM — in a zero‑downtime, 24/7 trading environment
• Integrate on‑chain data sources, wallet intelligence, and crypto market signals into LLM‑powered analytical pipelines — building the data layer that makes Binance’s agents genuinely crypto‑native
• Partner with research scientists to translate experimental findings into production‑grade agentic solutions with clear performance benchmarks

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, Statistics, Mathematics, or related technical field
• 0–5 years of industry or research experience in applied ML or AI engineering
• Strong Python programming skills ; Equally important: demonstrated comfort with vibe coding — using AI‑assisted development tools fluidly as core part of your workflow
• Demonstrated hands‑on experience with LLMs — prompt engineering, post‑training, or end‑to‑end LLM application development
• Familiarity with multi‑agent system design — task decomposition, tool use via MCP, memory management, parallel agent execution, and inter‑agent communication
• Strong analytical thinking and problem decomposition; comfortable operating under ambiguity in fast‑moving environments

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.

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.