AI/ML Engineer

📋 Description

• Design and implement training pipeline components for AI/ML models in risk decisioning.
• Develop, test, and iterate model features with senior support.
• Support offline evaluation and online experiment analysis of model performance.
• Write modular, testable code following engineering best practices.
• Collaborate with PMs, Engineers, and Risk to translate findings into actionable recommendations.
• Contribute to production model workflows: training, tuning, inference, monitoring.
• Apply AI/ML methods like generative AI and sequence models to improve risk decisioning.

🎯 Requirements

• 1-2 years of experience in applied data science or AI/ML engineering, incl. internship or project work.
• ML fundamentals: feature development, training, validation, tuning, evaluation.
• Familiarity with cloud platforms (AWS preferred), orchestration tools, and version control.
• Familiarity with offline evaluation, experimentation, and performance tradeoffs.
• Strong communication of analyses; collaborate with technical and non-technical partners.
• Nice to have: production ML workflows: inference, monitoring, retraining, deployment.
• Nice to have: AI-assisted dev tools (e.g., Cursor, Claude Code).
• Nice to have: deep learning methods like embeddings, sequence models, representation learning.

🎁 Benefits

• Hybrid work policy with four days in office and Fridays remote; location-based.
• In-office perks incl. backup child/elder/pet care; subsidized commuter benefit.
• 401k match and comprehensive medical, dental, vision, life, and disability benefits.
• Generous vacation policy and company-wide paid days off; 1% volunteer time off.
• Paid parental leave: up to 24 weeks for birthing and 12 weeks for non-birthing.
• Maven family planning with $15k lifetime reimbursement.