Staff Machine Learning Engineer, Credit Products
Radarblock is a user-first Web3 growth agency that helps crypto and blockchain protocols grow their communities, user bases, and market presence through content, campaigns, and partnerships. It has worked with clients such as Symbiotic, Linea, Polygon, Vana, Bungee, PrismaX, Covalent, Kite AI, and Avail.
Projects
About Radarblock
Radarblock is a user-first Web3 growth agency positioned around detecting and growing 'the protocols of tomorrow.' The agency offers services including content marketing, founders content, press releases, community building, campaign design and execution, strategy and positioning, partnership marketing, branding and design, and distribution channels and KOL management. They emphasize a battle-tested, onchain-data-driven approach to marketing rather than superficial engagement. Radarblock's clients and case studies include Symbiotic (230K+ community members onboarded), Avail ($2.5M+ daily liquidity pool volume), Morpho (UGC distribution campaigns), Agglayer (creator grants), Ghost/$GHST ($20M DAI unbonding curve campaign), Linea, Polygon, Vana, Bungee, PrismaX, Covalent, and Kite AI. The agency reports having built 25+ communities, executed 500+ campaigns, helped clients raise over $900M, and worked with 50+ clients whose products reach 10M+ users combined. They also publish research content such as a 'State of Crypto x AI 2026' report.
Skills
About the Role
You will own the full credit modeling stack from data ingestion through production decisioning. You will evaluate alternative external data signals and apply rigorous scientific methods to underwrite new customer segments. You will design, build, and deploy models into production, scale data pipelines and MLOps infrastructure, and troubleshoot real-time model issues. You will identify and implement material improvements to credit policy and balance rapid innovation with regulatory and compliance requirements.
Requirements
- Minimum of 8 years related experience with a Bachelor's degree or 6 years with a Master's degree or PhD with 3 years experience developing and deploying ML and statistical models in production
- Degree in a technical field such as Computer Science, Mathematics, Statistics, Physics, or Engineering
- Strong quantitative intuition and data visualization skills
- Full-stack proficiency across data pipelines and production-grade software architecture
- Ability to communicate clearly with technical and non-technical audiences
- Pragmatic problem-solving approach balancing business, technical, and regulatory constraints
- Familiarity with tree-based models and gradient boosting (helpful but not required)
Responsibilities
- Underwrite new customer segments using rigorous scientific methods
- Lead ML operations and infrastructure initiatives
- Design and implement the full credit modeling stack
- Leverage new data sources for modeling using data science techniques
- Identify and execute material improvements to credit policy
- Support model updates and troubleshoot production issues
- Operate within regulated banking constraints balancing innovation and compliance
Benefits
- Remote work
- Medical insurance
- Flexible time off
- Retirement savings plans
- Modern family planning