About Cred Protocol
Cred Protocol's on a mission to bring DeFi lending to a billion people. Improving access to financial resources means quantifying risk. Quantified risk at scale is credit scoring. Cred Protocol's building one of the first decentralized credit scores, a DeFi primitive that unlocks capital-efficient lending and enables under-served communities to access the power of DeFi lending.
We're funded by top crypto investors including AllianceDAO, Volt Capital, Robot Ventures, GSR Markets, DCG Expeditions, SNZ Holding, AngelDAO, imToken and amazing founders and executives from across web2 and web3.
We’re a team of prior founders with successful exits and deep expertise in massively scalable infrastructure, AI, and blockchain with experience spanning Silicon Valley startups and world-class institutions such as Facebook/Meta, Amazon, Deutsche Bank and Cambridge University.
Role
Working closely with our data engineering team, you'll be the subject matter expert for machine learning as we move from initial MVP to scaled machine learning operations. You'll design an implement an enterprise-grade machine learning infrastructure covering credit risk modeling and fraud detection based on blockchain data. You'll be responsible for feature engineering, model training, deployment into production and iteratively testing and improving models over time.
Responsibilities
- Create and communicate a vision for modeling blockchain lending risk at DeFi scale.
- Plan and prioritize our machine learning platform roadmap, taking us from MVP to scale.
- Hire and inspire machine learning engineers to implement our ML platform roadmap.
- Create a high trust, empathetic team environment pursuing excellence with integrity.
- Manage and mentor the machine learning team.
- Communicate and coordinate across related functional areas such as Data Science, Data Engineering, Web3 Engineering (Smart contract and Oracle engineering).
- Inform and educate internal and external stakeholders through writing and speaking engagements.
Ideal candidate
- Excited by decentralized finance's potential to rebuild traditional finance on blockchain rails that are fundamentally fairer and more transparent.
- Comfortable learning and using new technologies.
- 3+ years hands-on experience implementing machine learning and deep learning .
- 3+ years deploying and improving ML models in a scaled production environment.
- 5+ years using agile development methodologies.
- Ability to work with little guidance and find paths forward.
- [Bonus] Experience training XGBoost machine learning models + deploying to production.
- [Bonus] Experience training Graph Neural Network models.
- [Bonus] Hands-on smart contract development (on Ethereum blockchain).
- [Bonus] Experience working in another crypto startup or protocol.
- [Bonus] Experience working in fraud detection, lending or credit risk modeling.
Benefits
- Generous equity packages.
- Generous comp.
- Unlimited time off.
- Flexible hours.
- Healthcare where needed.
- Visa sponsorship where needed.