Staff AI Scientist

Overview

About the team

Foresight builds advanced AI technology that turns Intuit’s proprietary data and financial domain expertise into experiences that deliver real customer value. We build the foundational models and agentic systems behind Intuit’s financial intelligence systems, and behind Financial Intuit Language Models, our family of fine-tuned models for financial intelligence. Our work reaches millions of small and medium-sized businesses across QuickBooks and products, and is grounded in the richness of data few companies might have

Job Overview

We are seeking a visionary and hands-on Staff AI Scientist to help shape the next generation of foundational language models and agentic systems that empower small and medium-sized businesses to thrive. In this role you will define, design, and build groundbreaking AI solutions that understand, reason, and act across complex financial and business contexts.

You will collaborate closely with cross-functional experts across AI research, data science, engineering, and product to create intelligent agents that help SMBs automate financial tasks, make smarter decisions, and operate more efficiently. Your work will combine scientific rigor with visionary execution, balancing theoretical innovation with large-scale practical impact.

As a Staff Scientist you set technical direction beyond your own projects. You are a builder-scientist — a creative thinker who develops novel model architectures and training paradigms and also drives their implementation and validation in real-world applications — and you raise the scientific bar for the teams around you. You will help shape the AI foundation that powers transformative products serving millions of customers.

Responsibilities

• Set technical direction. Define the technical strategy and roadmap for next-generation agentic and foundation-model systems, and drive innovation and scientific excellence across the organization.
• Build foundational models and agents. Design and develop foundational language models and agentic architectures that power intelligent decision-making for small and medium businesses.
• Advance the science. Explore novel approaches in large-scale pretraining, fine-tuning (SFT and RLFT/GRPO), retrieval-augmented generation, and reasoning to improve factuality, adaptability, and alignment.
• Solve real financial work. Build intelligent agents that understand financial data, customer context, and business workflows — from bookkeeping and autonomous accounting to planning, communication, and insight generation.
• Leverage Intuit’s data moat. Turn Intuit’s unique ecosystem signals — counterparty behavior, two-sided transaction visibility, and business twins — into defensible modeling advantages.
• Ship end-to-end. Take work from experimentation to production, owning evaluation frameworks and metrics that prove real-world impact.
• Elevate others. Mentor scientists and engineers, review technical designs, and grow the craft of the wider team — a core expectation at the Staff level.
• Collaborate across functions. Partner with AI research, engineering, product, and design to translate breakthrough science into scalable products used by millions.
• Share knowledge. Publish and present research findings, internal innovations, or contributions to open-source frameworks where appropriate.
  
  

• Ph.D. or Master’s degree in Computer Science, Math, Machine Learning, AI, or a related field, with a track record of technical leadership on complex AI systems.
• Proven experience with LLMs, multimodal, or foundation models — including pretraining, fine-tuning, and deployment.
• Deep understanding of transformer architectures, reinforcement learning, reasoning models, and agentic systems.
• Strong proficiency in Python and modern ML and agentic frameworks .
• Demonstrated ability to build end-to-end AI pipelines, from experimentation to production at scale.
• Experience influencing technical direction across multiple teams and mentoring other scientists and engineers.
• Excellent problem-solving, collaboration, and communication skills.
• A passion for creating AI that augments human potential and simplifies complex business workflows.
  
  

• Experience applying RL fine-tuning (GRPO, RLHF/RLFT) or model-based RL to language or decision-making systems.
• Background in financial, accounting, or business-domain AI, or in probabilistic forecasting and world models is a major advantage.
• Publications at top ML venues or meaningful open-source contributions.