We're seeking for a candidate who is passionate about software to join Intel as a Student Worker. This is a part time position for a candidate that is currently studying towards a relevant Bachelor, Licenciatura or Masters degree from a relevant academic institute.
In this position, you will be joining the Manufacturing Automation Industrial Systems organization as part of one of our Agile Teams where you will learn and perform a wide variety of activities part of the Machine Learning Stack within the robotics program, supporting validation of models and dataset creation and any other activities that will support the lifecycle.If you have passion not only to learn and grow in your career, but also contribute to enrich the life of every person on earth, we have a place for youBehavioral traits:
Self-learning attitude that drives to keep up with the technology
Can-do attitude
Open to identifying, picking up ownership and developing skills in areas outside of immediate scope
Attention to detail
NOTE: In order to be considered for this position, please submit your most updated resume in English.
You must possess the following minimum qualifications to be initially considered for this position. Preferred qualifications are in addition to the minimum requirements and are considered a plus factor in identifying top candidates. Experience listed below would be obtained through a combination of your schoolwork/classes/research and/or relevant previous job and/or internship experiences.
Minimum Qualifications
Must be an active student pursuing a Bachelors, Licentiate, or Master's degree in Computer Science OR related engineering fields.
3 to 6 months of university course work and/or projects with python and/or C++.
Upper Intermediate to Advanced English level (write, read and speak).
Must have permanent-unrestricted right to work in Costa Rica.
Preferred Qualifications
Experience with AI/ML tools/techniques are an added advantage
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. * Job posting details (such as work model, location or time type) are subject to change.