Drimva

Intuit

Principal AI Scientist - DGX

$274K–$370K

Mountain View, California · Principal · Full-time · Posted Oct 15, 2026

Experience
3+ years in AI Science leadership or management; 6+ years working with large datasets and databases; 6+ years with a general-purpose programming language.
Education
PhD/MS in Engineering Mathematics, Statistics, Theoretical/Computational Physics, or related field.

About the job

Leads AI science teams and hands-on development of machine learning models and capabilities for marketing, sales, and other business problems, from strategy and architecture through delivery.

What you'll do

  • Lead AI science work, develop foundational methods and novel applications, and build new capabilities for critical business problems.
  • Shape multi-year product and technology strategy, influence business leaders, and drive ML platform architecture decisions.
  • Lead teams and partners through ML solution delivery and integration; conduct design reviews and mentor colleagues.

What they ask for

  • PhD/MS in Engineering Mathematics, Statistics, Theoretical/Computational Physics, or a related field.
  • 3+ years as either a lead in an AI Science role or in a management position in AI Science.
  • 6+ years’ experience manipulating large datasets and using databases; 6+ years’ experience with a general-purpose programming language.
  • Expert knowledge and hands-on experience with ML pipelines, processes, and design patterns; hands-on expertise in one or more of ML, NLP, Statistics, or Optimization.

Nice to have

  • Prior experience or qualifications in Marketing platforms or media management.
  • Background in Cognitive sciences or Human Psychology, including group behavioral sciences.

Pay

Mountain View $273,500 - $369,500 (base salary)

Tools

ML, NLP, Statistics, Optimization, R, SQL, S-Plus, Python

AI focus

Develops and deploys machine learning models using analytical algorithms and deep learning, including applications in marketing audiences, brand management, generative engine optimization, price optimization, creative generation and optimization, and digital twins.

Model-written summary · the original posting is authoritative

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