Job DescriptionWe are looking for talented students interested in Computer Science and Software Engineering in the Deep Learning area. You will join the Neural Network Compression Tools team in OpenVINO organization. In this position, you will be involved in the development of the Neural Network Compression Framework (NNCF). The responsibilities will include exploration and development of state-of-the-art (SOTA) compression algorithms for neural network inference optimization in OpenVINO. You will have an opportunity to learn SOTA models and architectures, compression algorithms, the most popular frameworks and get knowledge of Intel platforms specifics. 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 - Preferred major: Math, Computer Science or Physics - Python or C/C++ programming skills Optional: - Knowledge of Machine Learning / Neural Networks, Image Processing / Computer Vision - PyTorch, TensorFlow, OpenVINOInside this Business GroupThe 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 StatementAll 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.BenefitsWe 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 ModelThis 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.