Senior Machine Learning Engineer

$161,500 - $219,000/Yr

Intuit - Mountain View, GA

Full-time - Senior

Mountain View, GA

10,001+ employees

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

About the position

The Senior Machine Learning Engineer at Intuit will be an integral part of a dynamic team of data scientists, responsible for developing and deploying data science models at scale. This role emphasizes collaboration with data scientists to refine features, build pipelines, and implement machine learning algorithms, while also engaging in statistical analysis and A/B testing to evaluate model performance. The position requires a strong foundation in data science tools and principles, as well as effective communication skills to convey complex technical concepts to diverse audiences.

Responsibilities

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

Requirements

• BS, MS, or PhD 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 understanding of machine learning techniques including classification, regression, and clustering.
• Familiarity with machine learning principles such as training and validation.
• Knowledge of data query and processing tools like SQL.
• Strong foundation in computer science fundamentals including data structures and algorithms.
• Experience with software engineering practices, including version control systems like Git.
• Experience deploying scalable software for millions of users.
• Familiarity 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.

Benefits

• Competitive compensation package
• Cash bonus eligibility
• Equity rewards
• Comprehensive benefits package