Staff AI Scientist — Lead End-to-End ML & NLP Solutions

Intuit; Mountain View (CA); On-site; USD 210,000 - 284,000; Full time

Benefits offered by this job

Bonus potential

Equity rewards

Job summary

Intuit in Mountain View, CA, is seeking a Staff AI Scientist to lead AI initiatives within the CG AI Team. You will design end-to-end model architectures, collaborate with product managers, engineers, and designers, and align model metrics with business goals to improve customer experiences.

This hands-on technical leadership role requires strong ML expertise, collaboration, and the ability to mentor other AI scientists while driving experiments, A/B tests, and scalable, data-driven decisions in

Qualifications

• BS, MS, or PhD in Computer Science, Statistics, Mathematics, Economics, Operations Research, or related quantitative field.
• 4+ years of industry experience in AI Science, Machine Learning, or related field.
• Strong experience with optimization techniques (combinatorial, gradient-based, Bayesian), NLP, and Explainable AI.
• Proficiency in Python, Scala, Java, and/or R.
• Strong SQL, Hive, SparkSQL skills; comfort working in Linux environments.
• Demonstrated ability to build reusable, end-to-end ML pipelines.

Responsibilities

• Collaborate with stakeholders to define success criteria and align model metrics with business goals.
• Lead scrum teams, design model solutions, and drive end-to-end architecture.
• Perform hands-on data analysis, ETL, and feature engineering with large datasets.
• Apply data mining, NLP, and machine learning paradigms to real-world problems.
• Design and run A/B tests; communicate impact and recommendations to leadership.
• Stay current with ML advancements and evaluate new techniques for customer-facing applications.
• Mentor and provide technical direction to other AI Scientists on the team.

Job description

Intuit in Mountain View, CA, is seeking a Staff AI Scientist to lead AI initiatives within the CG AI Team. You will design end-to-end model architectures, collaborate with product managers, engineers, and designers, and align model metrics with business goals to improve customer experiences.

This hands-on technical leadership role requires strong ML expertise, collaboration, and the ability to mentor other AI scientists while driving experiments, A/B tests, and scalable, data-driven decisions in