Drimva

Intuit

Senior Staff AI Scientist

$226K–$306K

Oakland, California +1 · Senior Staff · Full-time · Posted Oct 14, 2026

Location
Oakland, California
Mountain View, California
Experience
7+ years of industrial experience in Machine Learning, with 3 years in a technical lead capacity specifically focused on Ranking, Search, or Recommendation Systems.
Education
MS in Computer Science, Mathematics, Statistics, Physics or a related quantitative discipline.

About the job

Leads AI Science strategy and develops large-scale ranking and recommendation systems that personalize financial products for Credit Karma members.

What you'll do

  • Lead design and evolution of machine-learning models for user intent, financial journeys, engagement, ranking, and recommendations.
  • Set technical direction and standards, mentor scientists, and partner with product and engineering on roadmaps and production systems.
  • Identify personalization and targeting opportunities and communicate technical work and business impact to executives and external audiences.

What they ask for

  • MS in Computer Science, Mathematics, Statistics, Physics, or a related quantitative discipline.
  • 7+ years of industrial experience in Machine Learning, including 3 years in a technical lead capacity focused on Ranking, Search, or Recommendation Systems.
  • Track record designing and deploying high-scale, multi-stage ranking pipelines in production.
  • Ability to communicate technical complexity to executives and influence product, business, and engineering stakeholders.

Nice to have

  • Experience with multi-objective optimization and ranking systems balancing business and user goals.
  • Familiarity with survival analysis, time-series forecasting, or sequence-to-sequence modeling.

Pay

Oakland $226,000 - $306,000 (base salary)

Tools

Machine Learning, Ranking, Search, Recommendation Systems, deep learning, multi-objective optimization, survival analysis, time-series forecasting

AI focus

Builds intent-aware personalization and recommendation systems for financial products, including ranking, targeting, approval odds, and marketing optimization.

Model-written summary · the original posting is authoritative

First seen Oct 28, 2026 · Last verified Nov 5, 2026 (UTC)