About the job
Intuit's AI Research team develops novel AI/ML solutions that power intelligent experiences across Intuit's ecosystem of products. The team conducts applied and fundamental research across areas including decision-focused AI, probabilistic modeling, causal inference, simulation-based planning, agentic and multi-agent systems, neuro-symbolic AI, and LLM-based reasoning for business decision workflows, partnering with product and platform teams to translate research breakthroughs into customer value.
Responsibilities
Lead and define the research agenda in one or more focus areas, identifying high-impact problems and charting a path from exploration to impact
Conduct original research in decision-focused AI, probabilistic modeling, causal inference, simulation-based planning, agentic and multi-agent systems, neuro-symbolic AI, deep learning, and/or LLM-based reasoning for business decision workflows
Drive research programs across multiple concurrent workstreams, providing technical direction and ensuring coherence across projects
Publish research findings in top-tier venues and represent Intuit's research contributions to the broader scientific community
Collaborate with product and platform teams to translate research innovations into platform or customer-facing AI capabilities
Mentor junior researchers, elevating the team's technical depth and research quality
Identify and establish strategic research collaborations with academic institutions and external partners
Contribute to the team's intellectual culture through reading groups, seminars, and internal knowledge sharing
Qualifications
Minimum
PhD in Computer Science, Electrical Engineering, Statistics, Applied Mathematics, or a related field
8+ years of post-PhD research experience in AI/ML, with a strong record of publications in top-tier conferences and journals (e.g., NeurIPS, ICML, ICLR, AAAI, KDD, ACL)
Deep expertise in one or more of the following: decision-focused AI, probabilistic modeling, causal inference, simulation-based planning, agentic and multi-agent systems, neuro-symbolic AI, LLM-based reasoning
Strong fundamentals in deep learning, optimization, and statistical machine learning
Demonstrated ability to lead research projects and to provide technical direction across multiple projects and researchers
Proficiency in Python and ML frameworks (PyTorch, TensorFlow, or equivalent)
Strong communication and interpersonal skills; ability to influence across teams and present research to both technical and non-technical audiences
Track record of translating research into real-world impact in an industry setting
Preferred
Experience as a tech lead in research
Active engagement with the research community (program committees, reviewing, workshops)
Familiarity with Intuit's product domains: tax preparation, accounting, personal finance, or small business management