Tech Stack
ETLPythonPyTorchTensorflowWeb3
About the role
- Architect and train custom foundation LLMs optimized for trading, compliance, and Web3 data.
- Build next-generation multi-agent systems blending search, reinforcement learning, and LLM reasoning for real-world tasks.
- Collaborate on Web3 data-lake design including ETL pipelines, vector stores, and real-time feeds.
- Partner with product, compliance, and customer-support teams to deploy models in production.
- Surface new AI-Web3 use cases, prototype MVPs, and shepherd them toward scale.
- Ingest and reason over massive on-chain and off-chain datasets to power real-time insights.
- Design intelligent trading agents, signal generators, and strategy-optimization engines.
- Automate compliance, travel-rule enforcement, and on-chain forensics at scale.
Requirements
- Master's or PhD in ML, AI, Computer Science, Mathematics, or related field.
- Published in top conferences/journals (ICLR, NeurIPS, ACL, etc.) on foundational LLMs, agent frameworks, or reasoning architectures.
- Deep expertise in reinforcement learning, reasoning algorithms, or related paradigms; bonus if experience building or extending agentic frameworks.
- Fluent in Python; experience with PyTorch, TensorFlow, JAX, or similar; ability to prototype new model architectures end-to-end.
- Enthusiasm for finance engineering, blockchain protocols, on-chain data, DeFi mechanics, or regulatory landscapes.
ATS Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
machine learningartificial intelligencereinforcement learningreasoning algorithmsPythonPyTorchTensorFlowJAXETL pipelinesdata analysis
Soft skills
collaborationcommunicationproblem-solvingcreativityleadership
Certifications
Master's degreePhD