Overview As Distinguished AI Scientist, you will shape Intuit's AI-driven product portfolio by solving high-impact problems and advancing state-of-the-art AI research. You'll lead end-to-end development and deployment of new AI capabilities that create transformative customer experiences. Working across business units and platform teams, you will influence the long-term AI roadmap and mentor scientific talent. This role offers the chance to publish, patent, and contribute to Intuit's mission to enable prosperity through intelligent software. You will operate at scale, driving responsible AI and a culture of rigorous science.
Compensation / Benefits- competitive compensation
- cash bonus
- equity rewards
- benefits (as per company plans)
Responsibilities- Define and tackle Grand Challenges to unlock new AI-driven customer experiences
- Contribute to a multi-year technical roadmap with AI leadership to stay at the forefront of innovation
- Build end-to-end solutions that translate research into impactful products
- Collaborate with business units and platform teams to accelerate testing and deployment
- Ensure data quality, model evaluation, and lifecycle management through monitoring and retraining
- Champion responsible AI with fairness, transparency, and trustworthiness
- Mentor scientific talent and foster a culture of innovation, ethics, and rigor
- Share AI innovations with the scientific community via publications, patents, and talks
Key requirements- MS / Ph.D. in Computer Science, Statistics, or Applied Mathematics with AI/ML focus or equivalent experience
- Deep expertise in GenAI and LLMs; RL, LLM fine-tuning, and multi-modal models
- Proven AI research record with publications at leading venues
- 10+ years building and deploying AI solutions for meaningful customer impact
- Experience turning business requirements into prototypes using Python and frameworks like TensorFlow or PyTorch
- Ability to influence cross-functional strategy and deliver aligned solutions
- Excellent communication and collaboration to explain concepts to diverse audiences
- Experience with cloud ML platforms (AWS, GCP, or Azure) preferred
- Strong CS/DS fundamentals including data structures, algorithms, MLOps, A/B testing
- strong communication
- collaboration
- mentorship
- GenAI
- LLMs
- Reinforcement Learning
