Senior AI Scientist

Intuit

Confirmed live 2 days ago High trust

Quick summary

Work type: On-site
Location: Mountain View, CA
Salary: $180,000–$243,500 / yr
Posted: 10 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 $204k

This role $212k

$138k most similar roles pay here $258k

This role pays more than 60% of similar roles. Most pay $162,000–$246,150 — the shaded band above. At the midpoint, this role pays about $212k versus about $204k 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 · Senior AI Scientist

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As a Senior AI Scientist on the Virtual Expert Platform team, you will serve as the technical architect for recommendation and ranking systems that connect customers with expert guidance across multiple product verticals. You will own the end-to-end lifecycle of these models, including data discovery, feature engineering, production deployment, and A/B testing to balance immediate business value with long-term customer trust. Your daily work involves building multi-stage architectures for candidate retrieval and scoring while exploring emerging technologies like generative AI, reinforcement learning, and agentic architectures. To succeed, you must possess expert proficiency in Python, SQL, and frameworks such as PyTorch, TensorFlow, scikit-learn, pandas, and NumPy. You will also utilize Hive and Spark to manage large-scale data ecosystems while translating complex technical performance into actionable business outcomes for cross-functional partners.

Skills

Python SQL PyTorch TensorFlow scikit-learn Pandas NumPy Spark Hive SparkSQL Linux Recommendation Systems Deep Learning NLP Transformers Reinforcement Learning Generative AI ETL Pipelines

What you'll do

Design and deploy large-scale recommendation and ranking models to predict customer needs across multiple product verticals.
Architect multi-stage recommendation systems including candidate retrieval, scoring, re-ranking, and real-time blending.
Develop logic that balances immediate revenue with long-term customer trust and lifetime value.
Perform hands-on data discovery, ETL pipeline construction, and feature engineering for massive datasets.
Design and execute A/B tests to perform statistical analysis and communicate actionable insights to leadership.
Define key metrics to quantify revenue, engagement, and customer experience in collaboration with product teams.
Research and evaluate emerging technologies like generative AI and reinforcement learning to improve recommendation quality.

What we're looking for

MS or PhD in Computer Science, Statistics, Applied Mathematics, Operations Research, Physics, or a related quantitative discipline.
4+ years of industry experience building and deploying machine learning models in production environments.
Expert proficiency in Python and SQL with deep experience in PyTorch, TensorFlow, scikit-learn, pandas, and NumPy.
Strong experience with ranking, retrieval, and multi-stage recommendation architectures.
Solid foundation in statistical modeling and ML techniques including neural networks, decision trees, and recommender systems.
Proficiency working with large-scale data ecosystems such as Hive or Spark.
Ability to communicate complex technical concepts and link model performance to business outcomes for non-technical audiences.
Experience with deep learning, NLP/NLU, or agentic AI patterns is preferred.

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