Intel HPC (High Performance Computing) organization is responsible for managing and optimizing Intel's private global computing cloud, which is among the largest private clouds.

We are looking for a talented Machine Learning and Data Engineering student to join a leading data team to develop machine learning and data-oriented solutions, which will improve the quality and execution within our private cloud.

Our projects include timeseries predictions, anomaly detection, predictions (supervised and unsupervised), recommenders, optimization problems and more.

The work will involve end to end ownership of the projects - working with domain experts, using high volumes of data, researching ML algorithms, creating the solution and development.

The responsibilities include - developing new capabilities, integrating and deploying solutions, optimizing and supporting the global solutions

**Working in Hybrid mode**

#LI-HYBRID

Qualifications

Minimum Qualifications:

� Students for BSc/Ms.c in computer science, information systems or a related field.

� deep understanding of Machine Learning concepts and principles

� 2 Years till graduation

� Experience with Software development/ scripting or automation

� Availability for at least 2.5 days in a week

� Python development experience

Preferred Qualifications:

� Linux System knowledge

� DevOps

Inside this Business Group

The High Performance Computing (HPC) group within Intel's Accelerated Computing Systems and Graphics Group (AXG) defines, delivers, and markets products that are critical to customers in Cloud, Government, Academia, and Industrial market segments. These products help end customers gain insight into and discover solutions to their most important problems. AXG products enable a broad range of breakthroughs: from cutting edge film making and animation, to scientific discoveries, weather simulation, to success in investment banking, to breakthroughs in manufacturing from small businesses to the largest industries.

Work Model for this Role

This role will be eligible for our hybrid work model which allows employees to split their time between working on-site at their assigned Intel site and off-site.