Pioneer Talent Program - Applied Data Scientist

New
B
BinanceCrypto, AI
Location: Hong Kong; Singapore. Remote-first, work-from-home arrangement (may vary depending on the nature of the role and team)Full-TimeSenior
Salary not disclosed
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Job Details

Experience
0–5 years of industry or research experience in applied ML or AI engineering
Required Skills
PythonPrompt Engineering

Requirements

  • Hold a Bachelor's or Master's degree in Computer Science, Electrical Engineering, Statistics, Mathematics, or a related technical field.
  • Have 0–5 years of industry or research experience in applied ML or AI engineering.
  • Demonstrate strong Python programming skills.
  • Demonstrate hands-on experience with LLMs, including prompt engineering, post-training, or end-to-end LLM application development.
  • Be familiar with multi-agent system design, including task decomposition, tool use via MCP, memory management, parallel agent execution, and inter-agent communication.
  • Demonstrate comfort using AI-assisted development tools as part of your workflow.
  • Bring strong analytical thinking and problem-decomposition skills, and be comfortable operating under ambiguity.

Responsibilities

  • Design and implement production-grade LLM pipelines and agentic trading features, including reasoning agents, tool-selection frameworks, and autonomous workflows.
  • Improve agent understanding, reasoning, tool selection, and action execution while optimizing intelligence, latency, and reliability.
  • Build and maintain evaluation frameworks for reasoning model outputs in crypto contexts.
  • Apply test-time scaling techniques, including chain-of-thought, self-consistency, and process reward models.
  • Architect AI system components for inference latency, throughput, and cost efficiency using serving frameworks such as vLLM and TensorRT-LLM.
  • Integrate on-chain data sources, wallet intelligence, and crypto market signals into LLM-powered analytical pipelines.
  • Partner with research scientists to translate experimental findings into production-grade agentic solutions with performance benchmarks.
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