Staff AI Scientist (Lending)

Location: Mountain View, California, United States

Base pay: $209,500–$283,500 per year. The position may also be eligible for cash bonuses, equity rewards, and benefits.

Company

hirify.global is a financial technology platform offering products including TurboTax, Credit Karma, QuickBooks, and Mailchimp.

What you will do

• Develop machine learning and AI systems for credit risk underwriting, decisioning, loan pricing, limit assignment, portfolio monitoring, and collections.
• Evaluate emerging research and introduce machine learning methods that improve net credit loss and loss forecasting accuracy.
• Build and govern reusable credit data, feature assets, science infrastructure, and multi-stage agent pipelines.
• Design auditable, reproducible AI-first lending systems, including document intake, policy reasoning, and collections workflows.
• Lead complex research initiatives such as censored repayment modeling and causal pricing optimization, transferring results into production.
• Coordinate technical plans across Product, Engineering, Credit Risk, Analytics, Legal, and Model Governance while mentoring senior scientists and engineers.

Requirements

• BS, MS, or PhD in Computer Science, Statistics, Mathematics, Economics, or another quantitative field, or equivalent experience.
• 8+ years of experience building, deploying, and leading cross-functional production machine learning systems.
• Experience taking complex, high-stakes machine learning problems from concept to production with measurable business impact.
• Experience designing scalable data and feature platforms with versioning, quality contracts, lineage, and reproducibility.
• Strong communication skills for aligning Product, Engineering, and Risk stakeholders and communicating model designs to regulatory standards.
• Experience mentoring senior scientists and engineers.

Nice to have

• Deep expertise in credit risk, underwriting policy, limit assignment, risk-based pricing, or loss forecasting.
• Hands-on experience with LLMs and agentic systems, including orchestration, fine-tuning, retrieval-augmented generation, and evaluation.

Culture & Benefits

• Technical leadership role with approximately 70% of time dedicated to technical contributions.
• Opportunity to influence product and technology decisions across multiple lending teams.
• Competitive compensation with performance-based rewards.
• Potential eligibility for cash bonuses, equity rewards, and employee benefits.