Staff AI Scientist

Intuit

Confirmed live 2 days ago Trusted

Quick summary

Work type: On-site
Location: Mountain View, CA
Salary: $209,500–$283,500 / yr
Posted: 119 days ago
Freshness: Confirmed live 2 days ago
Nearby: 99+ roles within 25 mi

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Salary context

Competitive pay

How this pay compares to similar roles

Similar $225k

This role $246k

$167k most similar roles pay here $301k

This role pays more than 57% of similar roles. Most pay $189,525–$260,450 — the shaded band above. At the midpoint, this role pays about $246k versus about $225k for comparable roles.

Based on 240 similar postings.

Employer

About Intuit

Intuit is a financial software company known for products like TurboTax, QuickBooks, Mint, and Credit Karma, helping consumers and small businesses manage their finances and taxes. Industry: Financial Software & Technology

Intuit currently has 174 open roles on FindRole.

Listed pay typically runs $202,500–$274,000 across 152 roles with salary data.

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At a glance

TL;DR · Staff AI Scientist

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As a Staff AI Scientist on the GTM Tech platform AI team, you will join a collaborative group of scientists and engineers to build and deploy machine learning models. You will be responsible for developing solutions for marketing audiences, brand management, generative engine optimization, price optimization, creative generation, and digital twins. Your daily work involves performing hands-on data analysis, ETL, featurization, and designing end-to-end architecture while leading a scrum team to ensure high-quality code and implementation standards. You will utilize techniques such as NLP, Causal-ML, Reinforcement Learning, Bayesian Learning, and Deep Learning. The role requires proficiency in Python, Scala, Java, R, SQL, Hive, and SparkSQL within a Linux environment. You will solve complex marketing problems by applying advanced analytical tools to real-world datasets and conducting A/B tests to measure impact.

Skills

Machine Learning Deep Learning NLP Causal-ML Bayesian Learning Reinforcement Learning Python Scala Java R SQL Hive SparkSQL Linux ETL Explainable AI Combinatorial Optimization Gradient Methods

What you'll do

Build and deploy machine learning models using analytical algorithms and deep learning approaches.
Perform hands-on data analysis, including ETL processes and feature engineering for large datasets.
Apply advanced techniques like NLP, Causal-ML, Reinforcement Learning, and Bayesian Learning to real-world problems.
Lead the technical work of a scrum team by designing model solutions and end-to-end architectures.
Run A/B tests to measure the impact of models and communicate results to leadership.
Research and integrate new machine learning technologies from academia and industry into products.
Define success criteria and align model metrics with specific business goals in collaboration with stakeholders.

What we're looking for

BS, MS, or PhD in Statistics, Mathematics, Computer Science, Economics, Operations Research, or a related field.
4+ years of industry experience in AI science.
4+ years of hands-on expertise in ML paradigms including Causal-ML, supervised/unsupervised, Online, Bayesian, Reinforcement, or Deep Learning.
Proficiency in NLP techniques, Explainable AI, and various machine learning frameworks.
Proficiency in optimization paradigms such as combinatorial optimization, gradient methods, or Bayesian optimization.
Expertise in programming languages including Python, Scala, Java, and/or R.
Proficiency in SQL, Hive, SparkSQL, and working within a Linux environment.
Experience building end-to-end reusable pipelines from data acquisition to model output delivery.

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