Senior Deep Learning/Reinforcement Learning Engineer

We are looking for an experienced ML, Deep Learning & RL Engineer to join our team to conduct research, design, test and train deep learning and RL models in a cutting-edge use case. ● You will be entrusted with complex planning, coding and engineering duties ● You must have hands-on experience and deep knowledge in ML/DL & RL ● Reinforce the vision, purpose, and strategy of the team ● Identify underlying problems in current models and implement solutions ● Work with Deeplink’s engineering, product and research team to design, develop, validate, deploy, and manage ML/RL systems ● Research and implement ML/RL algorithms and tools ● Pick appropriate data representation methods Your deliverable will be: ● Building a Uniswap SORA (smart order router agent) About us Deeplink is an Ethereum-based deep-learning protocol allowing blockchains to maintain On-chain Neural Networks while introducing programmability, machine learning and on-chain data science into blockchains. In addition, other Ethereum or EVM compatible chains and protocols can use on-chain neural networks and agents to improve efficiency, on-chain execution capabilities and security. We are true believers in the spirit of crypto and blockchain—of economic Freedom, where everyone should have access to financial freedom. We are big believers in decentralisation, fairness & transparency. We live and breathe in crypto and blockchain 24/7. We are extremely passionate about building open-source tools to innovate. All Deeplink technology, engineering and technical concepts, research, codes, data and product development methodologies are public and open-source. About the use case Uniswap is the largest decentralised crypto exchange (or DEX) operating on the Ethereum blockchain. Uniswap’s average daily trading volume was US$220 million in October 2020, and today, it is responsible for over $1 billion. We estimate by 2024, decentralised exchanges will exceed the centralised exchanges by activities, volume and users. Uniswap’s large number of activities resulted in random requests, congested transactions, variable Uniswap fees, and variation in Ethereum gas fees. As a result, there are many inefficiencies in the Uniswap protocol/ecosystem. For example, consider a bustling Sunday market where buyers and sellers meet to exchange goods and services whereby things can go incredibly wrong during rush hours. Uniswap traders often spend significant slippage and unnecessary protocol and Ethereum gas fees. There are three main users/stakeholders; ● Traders ● LPs (liquidity providers) ● The Uniswap project (protocol) Deeplink v2 is built using deep reinforcement learning to simulate a real-world Uniswap environment/different scenarios (HTR, UTS, low and high supply & demand, high activities). With the vast amount of L3 Atom’s historical and live Uniswap data, Deeplink can simulate different market conditions in parallel. The DRL policy will define inefficiencies and rules. Agents will be punished as they spend more fees when choosing inefficient trade routes. The principle of this video is an excellent inspiration for Deeplink Uniswap SORA [login to view URL] Key Benefits of the Role: ● To challenge yourself and build solid career advancement ● Be at the forefront of an exponentially growing industry with cutting-edge technology ● Build a professional network and meet like-minded people ● Competitive salaries, bonuses and other financial incentives What do we expect from you: ● Excellent communicator ● Be open-minded and eager to learn ● Commitment to excellence ● A team player ● Offering quality to all stakeholders ● Thinking out of the box - a true innovator If interested in this great opportunity, please apply as soon as possible. The applications will be closed on 26th July 2022.