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Arrakis Finance
Blockchain Engineer R&D
3 months ago | 138 views | 6 applications

Blockchain Engineer R&D

Full-time
Remote

About the company

Arrakis aims to disrupt the current market-making industry by providing the infrastructure to enable every project in the world that wants to launch a token to benefit from non-custodial, trust-less, and automated on-chain market-making strategies. We believe in a world where every organization, from a small startup to a large enterprise, will be tokenized and traded on-chain. For this world, Arrakis is building the tools to create the necessary liquidity to enable this token economy to rival and out-compete the traditional financial industry.

Job Summary

What you’ll accomplish

Primary Tasks: 📍Write research papers and whitepapers of future Arrakis products 📍Create comprehensive presentations for internal discussions and for talks in research conferences 📍Work closely with our CTO on technical specifications and protocol designs 📍Design and implement automated strategies for liquidity provision Train and backtest Machine Learning models 📍Design, build and test smart contracts, including Uniswap V4 Hooks Secondary Tasks: 📍Perform internal auditings of smart contracts 📍Collaborate with the frontend team to integrate smart contracts to a UI 📍Work with the backend team to monitor automated strategies

Academic requirements:

📍PhD in Mathematics or Quantitative Finance 📍Solid academic track, with research publications in top journals and talks in international conferences 📍Up to date knowledge of last DeFi research papers and protocols 📍Expertise in Advanced Probability and Stochastic Calculus 📍Theoretical and applied knowledge of Machine Learning/Data Science 📍Experience with LaTeX and Inskcape to write academic papers

Tech requirements:

📍+1 year of experience in Blockchain development (Solidity, Hardhat, Foundry) 📍Blockchain deep understanding, including EVM 📍Deep knowledge of Uniswap V3 and Uniswap V4 smart contracts and libraries 📍Smart Contracts security principles 📍Machine Learning libraries (Python, Tensorflow, PyTorch, Scikit-learn) 📍React, Typescript, Wagmi and Viem for frontend integrations AWS or GCP for backend integrations

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