Job Description

Come join our collaborative and creative group of AI scientists and machine learning engineers and build models that directly affect millions of our customers. In this role you will be building and deploying AI to drive product experiences.

Responsibilities

You’ll own building AI systems with a durable edge over commoditized AI, architecting systems that deeply leverage proprietary data, instituting comprehensive evaluation and monitoring, and leading research workstreams that produce meaningful publications and technology transfer to product teams.

Technical Skills & AI Science

• Stay current with the field and emerging research; recommend novel techniques that materially improve product metrics.
• Lead creation of reusable, versioned data and feature assets, and set data-quality standards across your area.
• Craft robust evaluation strategies, including adversarial and edge-case coverage.
• Lead the design of AI-first and agentic systems, owning the judgment call on when a problem calls for model training rather than prompting; architect multi-stage agent pipelines and reusable agent-driven infrastructure.
• Lead formulation of multi-component research problems where existing methods fall short, setting methodological standards across research workstreams.

Execution & Delivery

• Orchestrate complex initiatives by sequencing dependencies, communicating clear estimates, and managing risk across pivots.
• Identify and eliminate barriers from technical or prioritization complexity; reduce low-quality AI output through oversight and guardrails.
• Lead complex, ambiguous initiatives, partnering with Product, Analytics, Sales, and other stakeholders; drive end-to-end architecture and hold the team to high standards for code, design, and cost.

Customer Impact

• Frame customer problems, own customer solutions, and drive product thinking to deliver measurable, impactful value.
• Connect feedback, data, and usage signals from customers to identify latent needs.
• Design end-to-end customer workflows and scalable technical solutions, communicating with product, design, and PM partners; own the transfer of research outputs into product or platform contexts.

Collaboration & Team Growth

• Elevate the effectiveness of your team, other teams, and cross-functional partners; coach engineers to raise standards.
• Guide engineers on how to break work into pieces AI agents can execute reliably.
• Identify larger gaps in tech debt, tooling, and agent fluency that drive meaningful productivity gains.

Qualifications

• BS, MS, or PhD in Statistics, Mathematics, Computer Science, Economics, Operations Research, or equivalent work experience.
• 7+ years of industry experience with AI/data science.
• 7+ years hands-on expertise in ML paradigms (Causal-ML, supervised/unsupervised, Online, Bayesian, Reinforcement, Deep Learning).
• Proficient in multiple optimization paradigms, NLP techniques, explainable AI, and ML frameworks.
• Expertise in Python, Scala, Java, and/or R; efficient in SQL/Hive/SparkSQL; comfortable in Linux.
• Experience building end-to-end reusable pipelines from data acquisition to model output delivery; strong oral and written communication skills.

Intuit provides a competitive compensation package with a strong pay for performance rewards approach. This position may be eligible for a cash bonus, equity rewards and benefits, in accordance with our applicable plans and programs (see more about our compensation and benefits at Intuit®: Careers | Benefits). Pay offered is based on factors such as job-related knowledge, skills, experience, and work location. To drive ongoing fair pay for employees, Intuit conducts regular comparisons across categories of ethnicity and gender.

The expected base pay range for this position is:

Mountain View $209,500 - $283,500