Intern - GTO Tools

VMware - Palo Alto, CA4.1

InternshipEstimated: $80,000 - $110,000 a year
Business Summary:
VMware is a global leader in cloud infrastructure and business mobility. VMware accelerates customers’ digital transformation journey by enabling enterprises to master a software-defined approach to business and IT. With VMware solutions, organizations are building extraordinary experiences by mobilizing everything. Our customers are responding faster to opportunities with modern data and apps hosted across hybrid clouds, and safeguarding customer trust with a defense-in-depth approach to cybersecurity.

At the core of what we do are our people who deeply value execution, passion, integrity, customers, and community. Do you dare to do the stuff you’ve always dreamed about? Dare to explore at

VMware offers cutting-edge cloud infrastructure and security services to companies of all shapes and sizes. Our world is all about technology, and that world is growing because the imagination, ingenuity and talent of our teams knows no bounds. We believe that creativity sparks innovation and inspires our employees to think of VMware differently and change the world around them.

Job Role and Responsibilities:
We are searching for several talented, dynamic, hands on Data Scientists to be part of our team.

You will work closely with a team of software engineers and product managers on the design of prototypes of systems to demonstrate feasibility of proposed machine learning algorithms. Also, will assist with the design and implementation of machine learning pipelines (data ingestion, feature extraction, training, testing and validation, inference, and continual learning). And lastly, follow relevant work being done in academic and other research organizations; be as close as possible to the state-of-the-art in the fields of AI and machine learning.

Required Skills:
Experience in data science or machine learning working with large data sets
Strong coding skills; you’re proficient in Python and Spark and have a working knowledge of at least one of Scala, Java, or C++.
Proficient in Python statistical processing libraries such as NumPy, Pandas, SciPy, Scikit-Learn, etc.

Preferred Skills:
Experience working with deep learning frameworks such as TensoFlow, MXNet, Caffe2, or PyTorch
Familiar with large-scale data processing frameworks such as Apache Spark, and cloud computing environments such as Amazon Web Services (AWS).
Firsthand experience working with machine learning models and techniques such as decision tree, gradient boosted tree, random forest, ensemble methods, clustering, principal component analysis