Strong background in machine learning, including deep learning, unsupervised learning, or transfer learning techniques.
Proficiency in programming languages such as Python, JavaScript, or Solidity, along with experience working with machine learning libraries (e.g., TensorFlow, PyTorch) and Web3 frameworks (e.g., Web3.js, ethers.js).
Solid understanding of machine learning algorithms, statistical modeling, and optimization techniques.
Familiarity with Web3 technologies, such as blockchain platforms (Ethereum, Polkadot), decentralized finance (DeFi), decentralized identity (DID), or other relevant areas within the Web3 ecosystem.
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