AI Scientist 2

Responsibilities

• Explore, develop, and deploy machine learning models, contributing to the end-to-end ML lifecycle in partnership with machine learning engineers and guided by senior scientists.
• Apply various machine learning techniques (supervised, unsupervised, reinforcement learning, NLP, GenAI) to improve relevance and personalization algorithms, with an emphasis on understanding and implementing 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.
• Partnership with product managers and analysts to 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.

Qualifications

• MS, or PhD in an appropriate technology field (Computer Science, Statistics, Applied Math, Operations Research, etc.) or equivalent work experience.
• 1+ years of experience in modern AI/ML tools and proficient in Python and typical AI/ML libraries (e.g., TensorFlow, PyTorch, Keras).
• Familiarity with distributed computing frameworks (e.g., Spark, Ray) is a plus.
• 1+ years of experience in machine learning 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.
• Efficient in SQL
• Solid communication skills: Demonstrated ability to explain complex technical issues to both technical and non-technical audiences.

Intuit provides a competitive compensation package with a strong pay for performance rewards approach. This position may be eligible for a cash bonus, equity rewards and benefits, in accordance with our applicable plans and programs (see more about our compensation and benefits at Intuit®: Careers | Benefits). Pay offered is based on factors such as job-related knowledge, skills, experience, and work location. To drive ongoing fair pay for employees, Intuit conducts regular comparisons across categories of ethnicity and gender.