Machine Learning Engineer - 1

Overview

Responsibilities

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  Discover data sources, get access to them, import them, clean them up, and make them “machine learning ready”.
• Work with AI scientists to create and refine features from the underlying data and build pipelines to train and deploy models.
• Partner with AI scientists to understand, implement, refine and design machine learning and other algorithms.
• Run regular A/B tests, gather data, perform statistical analysis, draw conclusions on the impact of your models.

Qualifications

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  BS, MS, or PhD degree in Computer Science or related field, or equivalent practical experience.
• Knowledgeable with Data Science tools and frameworks (i.e. Python, Scikit, NLTK, Numpy, Pandas, Torch, TensorFlow, Keras, R, Spark).
• Basic knowledge of machine learning techniques (i.e. classification, regression, and clustering).
• Understand machine learning principles (training, validation, etc.)
• Knowledge of data query and data processing tools (i.e. SQL)
• Computer science fundamentals: data structures, algorithms, performance complexity, and implications of computer architecture on software performance (e.g., I/O and memory tuning).
• Software engineering fundamentals: version control systems (i.e. Git, Github) and workflows, and ability to write production-ready code.
• Mathematics fundamentals: linear algebra, calculus, probability
• Minimum experience of 1 year on relevant technologies

Intuit provides a competitive compensation package with a strong pay for performance rewards approach. This position will 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. The expected base pay range for this position is: