Job Details:
Job Description:
Intel CAIGC is committed to bringing AI from the cloud to end devices and building native on-device intelligent computing. Collaborating with global RnD teams and leading model developers, we connect LLMs/VLMs, AI Agents, media software stacks, and CPU/GPU/NPU hardware. We tackle core challenges in on-device model deployment and hardware-software co-optimization, and deploy cutting-edge multimodal AI capabilities onto massive PCs and end devices. We are looking for creative minds with curiosity, independent judgment, and a hands-on mindset to turn ideas into reality.
What You Will Do
Collaborate with top domestic model teams to drive the on-device deployment of LLMs, VLMs, image/video generation models and AI Agents
Rapidly prototype innovative ideas; develop inference pipelines, media codecs and automation tooling using Python / C/C++
Participate in the full lifecycle including technical evaluation, prototyping, system integration, performance tuning and product iteration
Conduct system-level hardware-software co-optimization targeting CPUs, GPUs and NPUs; explore new approaches to boost engineering efficiency powered by AI
Align with model, hardware and ecosystem stakeholders to scale cross-domain on-device AI solutions
Why Join Us
End-to-end full-stack exposure spanning models, Agents, system software, media processing and hardware acceleration
Full-cycle ownership - engage projects from initial prototyping all the way to product launch
Premium collaboration ecosystem - access leading model teams and Intel's global RnD network
Personalized career development - role alignment based on your interests and strengths
Mentorship guidance from experienced mentors
Pure engineering culture that encourages independent thinking and innovative experimentation
If you aim to go beyond surface-level exploration and translate AI innovations into end-user products used by hundreds of millions, come join us.
Qualifications:
What We Expect From You
Keep track of cutting-edge AI research with strong curiosity and self-motivation. Be adept at leveraging AI coding tools for efficient development, while possessing the judgment to audit and refine generated code.
Capable of breaking down complex problems, with the drive to evolve prototypes into production-ready deliverables.
Possess strong cross-team communication and collaboration skills.
Basic Requirements
Master's or PhD degree (exceptional bachelor candidates are also welcome); open to all majors.
Proficient in either Python or C/C++. Familiar with Windows or Linux development environments.
Prior experience including personal projects, AI practice or open-source contributions is preferred.
Candidates from diverse backgrounds (mathematics, physics, media studies, business, etc.) are welcome. We prioritize critical thinking, learning agility and the ability to implement ideas.
Preferred Qualifications
Hands-on experience building LLM/VLM/AI Agent applications, RAG and tool-use workflows
Familiarity with inference frameworks including PyTorch, OpenVINO and ONNX Runtime
Practical experience in model quantization, distillation, LoRA fine-tuning and on-device deployment
Experience with GPU/NPU acceleration, media processing, video codec and system performance optimization
Mature development workflows built around AI coding tools such as Cursor and GitHub Copilot
Job Type:
Student / Intern
Shift:
Shift 1 (China)
Primary Location:
PRC, Shanghai
Additional Locations:
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.
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