Senior Machine Learning Engineer

Intuit - Atlanta, GA

Full-time - Senior

Atlanta, GA

Computing Infrastructure Providers, Data Processing, Web Hosting, and Related Services

About the position

The Senior Machine Learning Engineer will be an integral part of a dynamic team of data scientists at Intuit, focusing on the conception, coding, and deployment of data science models at scale. This role requires a blend of technical expertise in machine learning and software engineering, along with strong communication skills to collaborate effectively with cross-functional teams.

Responsibilities

• Discover data sources, gain access, import, clean, and prepare data for machine learning.
• Collaborate with data scientists to create and refine features and build pipelines for model training and deployment.
• Partner with data scientists to understand, implement, refine, and design machine learning algorithms.
• Conduct regular A/B tests, gather data, perform statistical analysis, and draw conclusions on model impacts.
• Work cross-functionally with product managers, data scientists, and product engineers, communicating results effectively.
• Explore new technology trends to identify potential customer benefits.

Requirements

• BS, MS, or PhD degree in Computer Science or related field, or equivalent practical experience.
• 6+ years of experience in machine learning and data science.
• Proficient with data science tools and frameworks such as Python, Scikit, NLTK, Numpy, Pandas, TensorFlow, Keras, R, and Spark.
• Basic knowledge of machine learning techniques including classification, regression, and clustering.
• Understanding of machine learning principles such as training and validation.
• Familiarity with data query and processing tools like SQL.
• Strong foundation in computer science fundamentals including data structures, algorithms, and performance complexity.
• Proficient in software engineering fundamentals, including version control systems like Git and Github, and ability to write production-ready code.
• Experience deploying scalable software for millions of users.
• Experience with GPU acceleration technologies such as CUDA and cuDNN.
• Experience integrating applications with cloud technologies like AWS and GCP.
• Strong oral and written communication skills, with the ability to explain complex concepts to non-technical users.