Job Details:

Job Description:

Responsible for the design, development, testing, and performance tuning of AI kernels based on Intel GPU products; work will cover AI applications, algorithm research, kernel development, middleware, frameworks, operating systems, drivers, etc.

Qualifications:

Undergraduate or graduate students majoring in Computer Science or related fields
Familiar with the development and debugging of at least one programming language: C/C++/Assembly/Java/Python
Excellent written and verbal communication skills
Ability to proactively identify and resolve technical problems
Familiarity with mainstream deep learning frameworks, such as TensorFlow and PyTorch

          

Job Type:

Student / Intern

Shift:

Shift 1 (China)

Primary Location:

PRC, Shanghai

Additional Locations:

Business group:

The Software and AI (SAI) Team drives customer value by enabling differentiated experiences through leadership AI technologies and foundational software stacks, products, and services. The group is responsible for developing the holistic strategy for client and data center software in collaboration with OSVs, ISVs, developers, partners and OEMs. The group delivers specialized NPU IP to enable the AI PC and GPU IP to support all of Intel's market segments. The group also has HW and SW engineering experts responsible for delivering IP, SOCs, runtimes, and platforms to support the CPU and GPU/accelerator roadmap, inclusive of integrated and discrete graphics.

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.

Position of Trust

N/A

Work Model for this Role

This role will require an on-site presence. * Job posting details (such as work model, location or time type) are subject to change.