Staff Machine Learning Engineer

About This Role

Join the Consumer Group AI Team as a Staff Machine Learning Engineer, developing and deploying classic ML models and GenAI applications to enhance Intuit's TurboTax customer experience.

Responsibilities

• Discover, access, import, clean, and prepare data sources for machine learning
• Create and refine features from data and build pipelines to train and deploy machine learning models
• Understand, implement, refine, and design machine learning and other algorithms
• Build GenAI applications, such as AI agents
• Run regular A/B tests and performance evaluation pipelines to gather data, perform statistical analysis, and draw conclusions
• Work cross-functionally with product managers, AI scientists, and product engineers, and communicate results to peers and leaders
• Explore new technology shifts to determine customer benefit connections

Requirements

• 6+ years of experience in software development
• Knowledgeable with Data Science tools and frameworks (Python, Scikit, NLTK, Numpy, Pandas, TensorFlow, Keras, R, Spark)
• Basic knowledge of machine learning techniques (classification, regression, and clustering)
• Knowledge and experience of GenAI application development
• Understanding of machine learning principles (training, validation)
• Knowledge of data query and data processing tools (SQL)
• Computer science fundamentals (data structures, algorithms, performance complexity, I/O and memory tuning)
• Software engineering fundamentals (version control systems, Git, GitHub, production-ready code)
• Experience deploying highly scalable software supporting millions or more users
• Experience with integrating applications and platforms with cloud technologies (AWS and GCP)
• Strong oral and written communication skills

Qualifications

• BS, MS, or PhD degree in Computer Science or related field, or equivalent practical experience
• 6+ years of experience working in software development domain, with AI/ML related areas preferred

Nice to Have

• Experience with GPU acceleration (CUDA and cuDNN)

Skills

* Required skills

Benefits