Undergraduate Intern Technical (OpenVINO, Model Conversion team)

Job Description

In this position you will be a part of the OpenVINO Model Conversion team and will be responsible for conversion of the AI Framework model representation to the OpenVINO representation. Responsibilities are following but not limited to extending existing capability by adding new frameworks layers support and developing support of the new framework in the OpenVINO product. The position implies working at least 20 hours per week under a flexible schedule.

Qualifications

- Undergraduate university student working towards BSc or MSc: 3rd year or higher - Spoken and written English: intermediate level - Strong knowledge of Computer Science - C/C++ programming skills Optional: - Knowledge of Deep Learning / Neural Networks, Image Processing / Computer Vision - PyTorch, TensorFlow, OpenVINO - HF API / Transformers

Inside this Business Group

The Network & Edge Group brings together our network connectivity and edge into a business unit chartered to drive technology end to end product leadership. It's leadership Ethernet, Switch, IPU, Photonics, Network and Edge portfolio is comprised of leadership products critically important to our customers.

Posting Statement

All qualified applicants will receive consideration for employment without regard to race, color, religion, religious creed, sex, national origin, ancestry, age, physical or mental disability, medical condition, genetic information, military and veteran status, marital status, pregnancy, gender, gender expression, gender identity, sexual orientation, or any other characteristic protected by local law, regulation, or ordinance.

Benefits

We offer a total compensation package that ranks among the best in the industry. It consists of competitive pay, stock, bonuses, as well as, benefit programs which include health, retirement, and vacation. Find more information about all of our Amazing Benefits here.

Working Model

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. In certain circumstances the work model may change to accommodate business needs.