Senior Staff AI Scientist

Intuit

Confirmed live yesterday High trust

Quick summary

Work type
On-site
Location
Mountain View, CA
Salary
$226,000–$306,000 / yr
Posted
9 days ago
Freshness
Confirmed live yesterday

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $204k
This role $266k
$145k most similar roles pay here $323k

This role pays more than 90% of similar roles. Most pay $162,000–$246,237 — the shaded band above. At the midpoint, this role pays about $266k 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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View all roles at Intuit

At a glance

TL;DR · Senior Staff AI Scientist

As a Senior Staff AI Scientist within the QuickBooks Fintech team, you will develop probabilistic forecasting models to power cash flow prediction and financial forecasting for small businesses. You will design, implement, and train large-scale models end-to-end in code, collaborating with data pipeline teams to move models from concept to production-ready systems. Your daily work involves performing hands-on data analysis, including ETL, featurization, and data mining on large datasets. You will apply machine learning techniques such as supervised/unsupervised learning, Causal-ML, Online Learning, Bayesian Learning, Reinforcement Learning, and Deep Learning. Key technologies include modern deep learning frameworks and architectures like transformer-based forecasters such as TFT, DeepAR, or N-BEATS/N-HiTS. You will also build large-scale learned representations, manage technical scrum teams, and mentor others while navigating complex requirements for production latency and throughput constraints.

What you'll do

  • Design, implement, and train large-scale probabilistic forecasting models end-to-end in code.
  • Perform hands-on data analysis, including ETL, data cleaning, and feature engineering for large datasets.
  • Lead the technical work of a scrum team by designing model solutions and ensuring high-quality code standards.
  • Apply advanced machine learning techniques like NLP, Causal-ML, and Deep Learning to real-world financial problems.
  • Optimize models for production requirements including latency, throughput, and scalability.
  • Translate complex AI trade-offs and strategies into clear insights for both technical and non-technical leaders.
  • Mentor other scientists and engineers to promote innovation and craft excellence within the AI community.

What we're looking for

  • BS, MS, or PhD in Statistics, Mathematics, Computer Science, Economics, Operations Research, or a related field.
  • 8+ years of experience in applied ML/AI with a track record of delivering scalable, production-grade systems.
  • Deep hands-on experience building and training time-series or sequence models for multi-horizon probabilistic forecasting.
  • Strong grounding in probabilistic forecasting including quantile/distributional loss functions, calibration evaluation, and multi-task objectives.
  • Experience building large-scale learned representations at a scale of millions of entities, including cold-start strategies.
  • Proficiency with modern deep learning frameworks to build production training and inference pipelines.
  • Experience optimizing models for production latency and throughput constraints across real-time and batch scoring.
  • Excellent communication skills to collaborate with technical and non-technical stakeholders and influence organizational roadmaps.

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