AI Scientist 2

About the Role Intuit is seeking an AI Scientist to join a collaborative group of scientists and engineers to design and deploy next-generation AI and ML systems powering our omnichannel marketing platform. You will develop and deploy modern ML/AI models directly in our core product to address customer challenges, collaborating with product managers to shape innovative AI product experiences and drive meaningful impact. What You'll Do

• Explore, develop, and deploy machine learning models, contributing to the end-to-end ML lifecycle in partnership with ML engineers and guided by senior scientists.
• Apply various ML techniques (supervised, unsupervised, reinforcement learning, NLP, GenAI) to improve relevance and personalization algorithms, with emphasis on solutions that support broader AI initiatives.
• Collaborate with product managers, software engineers, and designers in designing experiments and minimum viable products, learning to integrate insights from advanced AI systems.
• Discover, process, and train on huge data sets.
• In partnership with product managers and analysts, run regular A/B tests, perform statistical analysis, draw conclusions on the impact of your models, and communicate results to peers and leaders.
• Research and explore new technology shifts, particularly in generative AI and advanced ML, to understand their potential connection with customer benefits and inform ongoing AI strategy. What We're Looking For
• MS, or PhD in Computer Science, Statistics, Applied Math, Operations Research, or equivalent work experience.
• 1+ years of experience with modern AI/ML tools and proficiency in Python and libraries (e.g., TensorFlow, PyTorch, Keras).
• Familiarity with distributed computing frameworks (e.g., Spark, Ray) is a plus.
• 1+ years of experience in ML techniques such as classification, regression, neural networks, large language models, recommender systems, natural language processing, clustering, anomaly detection, and computer vision.
• Understanding of MLOps principles and practices (e.g., version control, CI/CD for ML models) is a plus.
• Familiar with the latest trends and applications of generative AI including agentic applications. Nice to Have
• Experience deploying ML models in production environments and collaborating on end-to-end ML deployment pipelines. Compensation & Benefits
• Information not provided in the posting.