Intuit is looking to hire an ML Engineer to help conceive, code, and deploy data science models at scale using the latest industry tools. The role involves discovering data sources, preparing data for machine learning, building and refining models, and enhancing existing model performance.
Requirements
- Knowledgeable with Data Science tools and frameworks (i.e. Python, Scikit, NLTK, Numpy, Pandas, TensorFlow, Keras, R, Spark).
- Basic knowledge of machine learning techniques (i.e. classification, regression, and clustering).
- high-performance data processing
- machine learning algorithm exploration
- increasing the amount of data used to train the model
- automation of training and prediction
- orchestration of data for continuous prediction
Responsibilities
- Discover data sources, get access to them, import them, clean them up, and make them “machine learning ready”.
- Work with data scientists to create and refine features from the underlying data and build pipelines to train and deploy models.
- Partner with data 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.
- Explore new technology shifts in order to determine how they might connect with the customer benefits we wish to deliver.
- Build prototype models alongside data scientists. This may involve data exploration, high-performance data processing, and machine learning algorithm exploration.
- Works with data scientists to productionalize prototype models to the point where it can be used by customers at scale.
Other
- BS, MS, or PhD degree in Computer Science or related field, or equivalent practical experience.
- Work cross functionally with product managers, data scientists and product engineers, and communicate results to peers and leaders.
- Pay offered is based on factors such as job-related knowledge, skills, experience, and work location.
