At Equinix, we make the internet work faster, better, and more reliably. We hire talented people who thrive on solving hard problems and give them opportunities to hone new skills, try new approaches, and grow in new directions. Our culture is at the heart of our success and its our authentic, humble, gritty people who create The Magic of Equinix. We share a real passion for winning and put the customer at the center of everything we do.
We are looking for bright and enthusiastic college students who love to learn and want to make an impact on the world. Join the Equinix team and shape the future of cloud computing and enterprise connectivity at one of the Fastest Growing Technology Companies in America (Forbes).
The Equinix Internship Program offers wide-ranging opportunities in Information Technology, Engineering, Human Resources, Finance and more. Spend your time gaining practical work experience and learning from some of the sharpest minds in the industry. Work in a culture that thrives on innovation and delivering results, while building solid relationships with industry leaders, and fellow students from around the country.
- Advanced Predictive Analytics Platform
- Build predictive AI model to proactively identify potential Siebel application performance degradation/availability based on data collected from different layers of Siebel Enterprise (Network VM DB).
- Interns will have a hands-on experience on Java and Python.
- Interns will be involved in the Data Modelling phase which includes Data Translation and Data co-relation phases.
- Assist in the identifying the crucial Siebel CRM data points and assign weightage to the feature sets
- Identify the mapping attributes and then co-relate the different data sets based on the identifying mapping attributes
- Work on the POC for the predictive model based on the identified algorithm and experiment with the test data and feature sets
- Validate the outputs generated by the POC Model and come up with the accuracy rating of the predictive model
- Rising senior undergraduate student
- Intuitive understanding of machine learning algorithms (supervised and unsupervised modeling techniques)
- Experience with machine learning tools and libraries
- Intuition about algorithm, system performance and throughput
- Hands on experience on Linux, mining of structured, semi-structured, and unstructured data
- Java or Python scripting background
- Architecture and system/pipeline layout experience
- Deep learning
- Attention to detail, data accuracy, and quality of output
- Strong interpersonal, written, and verbal communication skills
- Ability to effectively function in a fast-paced environment
- Good to have:
- Experience with Apache Hadoop, Spark, SOLR/Lucene, Cassandra and related technologies
- Working knowledge of SQL
- Multimodal learning applications