Senior Staff AI Scientist

Intuit

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Quick summary

Work type: On-site
Location: Mountain View, CA
Salary: $226,000–$306,000 / yr
Posted: 56 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $202k

This role $266k

$131k $325k

below market most similar roles pay here above market

This role pays more than 90% of similar roles. Most pay $162,000–$241,750 — the blue band above. At the midpoint, this role pays about $266k versus about $202k 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 255 open roles on FindRole.

Listed pay typically runs $202,500–$274,000 across 236 roles with salary data.

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At a glance

TL;DR · Senior Staff AI Scientist

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The Senior Staff AI Scientist joins the QuickBooks Fintech team to build probabilistic forecasting models for cash flow prediction and financial forecasting for small businesses. This role involves designing, implementing, and training large-scale forecasting models end-to-end in code, while leading the technical work of a scrum team. Key responsibilities include performing hands-on data analysis, discovering data sources, and building featurization. The candidate will apply data mining, NLP, and machine learning techniques such as supervised/unsupervised learning, Causal-ML, Online Learning, Bayesian Learning, Reinforcement Learning, and Deep Learning. Required technical skills include experience with time-series or sequence models like TFT, DeepAR, or N-BEATS/N-HiTS, quantile or distributional loss functions, and modern deep learning frameworks. The work focuses on creating production-ready systems for financial intelligence.

Skills

Machine Learning Deep Learning NLP Probabilistic Forecasting Transformer TFT DeepAR N-BEATS N-HiTS Causal-ML Reinforcement Learning Bayesian Learning ETL Data Mining Git Scrum

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 featurization for large datasets.
Apply NLP, Causal-ML, and Deep Learning techniques to solve real-world financial problems.
Lead the technical work of a scrum team, including architecture design and code quality standards.
Optimize models for production latency, throughput constraints, and large-batch scoring.
Define success criteria and align model metrics with business goals alongside product and engineering teams.
Mentor other scientists and engineers to promote innovation and craft excellence within the AI community.
Communicate AI tradeoffs and strategies clearly to both technical and non-technical leadership.

What we're looking for

8+ years of experience in applied ML/AI with a track record of delivering scalable, production-grade AI systems.
BS, MS, or PhD in Statistics, Mathematics, Computer Science, Economics, Operations Research, or equivalent.
Deep hands-on experience building and training time-series or sequence models for multi-horizon probabilistic forecasting.
Strong applied grounding in probabilistic forecasting, including quantile or distributional loss functions and calibration evaluation.
Experience building large-scale learned representations, such as entity embeddings at millions-of-entities scale.
Strong fundamentals in a modern deep learning framework with experience building production training and inference pipelines.
Experience optimizing models for production latency and throughput constraints from real-time inference to large-batch scoring.
Excellent communication skills to work effectively with technical and non-technical partners, including risk and compliance stakeholders.

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