Intuit
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Machine Learning Engineer 2
role at
Intuit
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Overview In this role, you’ll be embedded inside a vibrant team of data scientists. You’ll be expected to help conceive, code, and deploy data science models at scale using the latest industry tools. Important skills include data wrangling, feature engineering, developing models, and testing metrics.
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.
Work cross functionally with product managers, data scientists and product engineers, and communicate results to peers and leaders.
Explore new technology shifts in order to determine how they might connect with the customer benefits we wish to deliver.
Qualifications
Model prototyping: build prototype models alongside data scientists, including data exploration, high-performance data processing, and machine learning algorithm exploration.
Model productionalization: productionalize prototype models to the point of customer scale, including automation of training and prediction.
Model enhancement: work on existing codebases to improve model prediction performance or reduce training time.
Machine learning tools: build tools to ease data science processes, such as speeding up training or simplifying data management.
BS, MS, or PhD degree in Computer Science or related field, or equivalent practical experience.
Knowledgeable with data science tools and frameworks (Python, Scikit, NLTK, NumPy, Pandas, TensorFlow, Keras, R, Spark).
Basic knowledge of machine learning techniques (classification, regression, clustering).
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. 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.
Expected base pay range for this position is:
Bay Area, California, CA: $137,500.00 – 186,500.00
Southern California, CA: $124,500.00 – 168,500.00
New York: $136,000.00 – 184,000.00
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Machine Learning Engineer 2
role at
Intuit
Get AI-powered advice on this job and more exclusive features.
Overview In this role, you’ll be embedded inside a vibrant team of data scientists. You’ll be expected to help conceive, code, and deploy data science models at scale using the latest industry tools. Important skills include data wrangling, feature engineering, developing models, and testing metrics.
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.
Work cross functionally with product managers, data scientists and product engineers, and communicate results to peers and leaders.
Explore new technology shifts in order to determine how they might connect with the customer benefits we wish to deliver.
Qualifications
Model prototyping: build prototype models alongside data scientists, including data exploration, high-performance data processing, and machine learning algorithm exploration.
Model productionalization: productionalize prototype models to the point of customer scale, including automation of training and prediction.
Model enhancement: work on existing codebases to improve model prediction performance or reduce training time.
Machine learning tools: build tools to ease data science processes, such as speeding up training or simplifying data management.
BS, MS, or PhD degree in Computer Science or related field, or equivalent practical experience.
Knowledgeable with data science tools and frameworks (Python, Scikit, NLTK, NumPy, Pandas, TensorFlow, Keras, R, Spark).
Basic knowledge of machine learning techniques (classification, regression, clustering).
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. 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.
Expected base pay range for this position is:
Bay Area, California, CA: $137,500.00 – 186,500.00
Southern California, CA: $124,500.00 – 168,500.00
New York: $136,000.00 – 184,000.00
#J-18808-Ljbffr