FLock.io is hiring Web3 Web3 Front-end Engineer
Web3 Front-end Engineer
Minimum 1 Year
Expertise in modern front-end technologies such as ReactJS, Vue.js, or Angular.
Familiarity with blockchain concepts and a keen interest in Web3 technologies.
Experience in integrating smart contracts and decentralized applications (DApps) within a user interface.
Strong understanding of UX/UI principles and a track record of developing engaging web interfaces.
Experience with Solidity or other smart contract languages.
Background in Python, especially if connected to machine learning implementations.
Involvement in open-source projects, particularly those related to blockchain or Web3.
Eagerness to learn and adapt in a rapidly evolving tech landscape, with a particular interest in federated learning and privacy-preserving technologies.
Duties & Responsibilities
- Developing and refining user interfaces for our platform, ensuring they are intuitive, responsive, and aesthetically pleasing.
- Collaborating closely with our back-end developers to ensure seamless integration of web services and APIs.
- Implementing and maintaining robust security measures in the front-end architecture, particularly focusing on safeguarding data in Web3 environments.
- Staying updated with the latest Web3 developments and integrating these advancements into our front-end systems.
- Crafting interactive elements that enhance user engagement with blockchain-enabled features.
- Leading the charge in creating accessible, user-friendly interfaces for interacting with our blockchain and federated learning functionalities.
Who We Are:
At FLock (flock.io), we are at the forefront of integrating Federated Learning with Blockchain technology. Our goal is to establish a decentralized network that collectively works towards a unified objective. We're leading the charge with the world's inaugural on-chain privacy-preserving neural processor, targeting the critical balance between the increasing demand for data and the risks of data breaches.
The FLock platform enables data owners to train machine learning models while maintaining the confidentiality of their source data. This is achieved through a system that ensures a transparent and decentralized consensus on outputs. Our solution stands out for its commitment to privacy, efficiency in bandwidth usage, and interoperability across various entities. Discover more about our innovative approach in our award-winning academic paper featured at the NeurIPS 2022 workshop, available here, and in our explanatory video here.
Join Our Team:
We are excited to expand our team with dedicated AI and Blockchain Engineers who are eager to bring the innovative concepts from our in-house academic research into real-world applications.