AI Tutor - Crypto

xAI xAI · AI Frontier · Remote · Financial

Role focused on providing high-quality annotations, evaluations, and expert reasoning to train and refine frontier AI models, specifically in the domain of cryptocurrency quantitative trading and digital asset markets. Involves generating diverse data formats (text, voice, video) and critiquing model outputs.

What you'd actually do

  1. Utilize proprietary software to deliver accurate labels, rankings, critiques, and in-depth solutions on assigned projects
  2. Consistently produce high-quality, curated data adhering to rigorous technical and domain standards
  3. Partner with engineers and researchers to iterate on new training tasks, evaluation frameworks, and crypto-specific benchmarks
  4. Offer actionable feedback to enhance the efficiency, accuracy, and usability of annotation and data-collection interfaces
  5. Identify and solve challenging problems from crypto & digital asset domains where you have strong expertise — examples include: - Provide rigorous critiques of model outputs, alternative quantitative approaches, mathematical derivations, code snippets, and step-by-step crypto reasoning

Skills

Required

  • Master’s or PhD in a quantitative discipline (Quantitative Finance, Financial Engineering, Computer Science (with crypto/blockchain focus), Statistics, Applied Mathematics, Economics (quantitative), Physics, Operations Research, Data Science, or closely related field) or equivalent professional experience as a quantitative crypto trader, systematic strategist, or on-chain analyst
  • Superior written and verbal English communication (technical papers, explanatory breakdowns, professional correspondence)
  • Extensive hands-on familiarity with crypto data sources and tools (CoinGecko, CoinMarketCap, Dune Analytics, Glassnode, Nansen, Chainalysis, Messari, DefiLlama, The Graph, blockchain explorers, CEX APIs, on-chain datasets, etc.)
  • Outstanding analytical skills, attention to detail, and sound judgment under partial information
  • Strong passion for cryptocurrency markets, blockchain technology, decentralized finance, quantitative methods, and frontier AI applications in digital assets

Nice to have

  • Professional experience in quantitative crypto trading, systematic strategies, or on-chain research at a crypto hedge fund, prop desk, market-making firm, DeFi protocol, or digital asset investment firm
  • Publications or public analyses in crypto quant topics (e.g., journals, conferences, reputable blogs, GitHub repos with notable traction)
  • Teaching, mentoring, or content-creation experience in crypto/quant finance (university, bootcamps, Twitter threads, newsletters)
  • Proficiency in Python for crypto analysis (pandas, NumPy, ccxt, web3.py, etherscan APIs, polars, scikit-learn, PyTorch/TensorFlow for ML models, etc.) and/or Rust/Solidity familiarity
  • Experience with backtesting crypto strategies, handling tick-level or on-chain data, managing API rate limits, and dealing with 24/7 market quirks
  • Knowledge of MEV, flash loans, oracle manipulation risks, liquidation cascades, or other crypto-native phenomena
  • CFA, FRM, CQF, or blockchain-specific certifications (e.g., Certified Blockchain Expert)
  • Prior involvement with LLMs, reinforcement learning, or AI evaluation

What the JD emphasized

  • quantitative crypto strategies
  • on-chain analysis
  • DeFi protocols
  • perpetual futures & derivatives trading
  • cross-exchange arbitrage
  • market microstructure
  • MEV-aware execution
  • machine learning for crypto alpha signals
  • portfolio/risk management
  • quantitative discipline
  • quantitative crypto trader
  • systematic strategist
  • on-chain analyst
  • crypto data sources and tools
  • quantitative crypto trading
  • systematic strategies
  • on-chain research

Other signals

  • training AI models
  • evaluating AI models
  • expert reasoning for AI
  • quantitative crypto analysis