AI Software Engineer Intern

Intel is hiring an AI Software Engineer Intern in Shanghai, China. Level rates it ; you can apply on Level.

Level's read on this job

On Level's scale, this software engineer role is Builds AI ●●●●: the job is building AI systems.
The posting mentions PyTorch, Python and AI agents among its tools and skills.
Level classes it as an internship.
Intel has 732 other open roles on Level.
This posting went up in the last few days.

AI in this role

Develop and optimize AI Agent core frameworks, runtimes, and execution pipelines as a graduate intern.

pytorchpython

ai-agentsdeep-learningllm-inferenceperformance-optimization

Job Details:

Job Description:

AI Agent Core Framework Development and Performance Optimization
Design, develop, and optimize AI Agent runtimes, agent kernels, and task execution frameworks. Research planning, reasoning, tool invocation, and execution mechanisms for agents in complex task scenarios, continuously improving execution efficiency, system reliability, and scalability.
Agent Core Infrastructure and Capability Development
Develop and enhance core Agent components, including workflows, memory systems, tool usage, and multi-agent collaboration. Optimize context management, task orchestration, state management, and execution pipelines to improve autonomous operation and decision-making capabilities in complex environments.
Agent Performance Analysis and Production Deployment
Build performance evaluation, profiling, and monitoring frameworks for Agent systems. Identify and resolve performance bottlenecks in large-scale and complex workloads, and drive the adoption of Agent technologies in areas such as software engineering productivity, intelligent operations, and automated engineering workflows.

Qualifications:

Basic Requirements

Master’s or PhD student in Computer Science, Artificial Intelligence, Software Engineering, or a related field
Proficient in Python with solid coding skills and good software engineering practices
In-depth understanding of at least one area in deep learning systems or large model inference, including but not limited to:
- PyTorch / TorchDynamo / FX / Inductor
- LLM inference workflows (e.g., KV cache, prefill / decode stages)
Understanding of large language models beyond API-level usage, including inference behavior, performance bottlenecks, and engineering constraints
Strong problem decomposition skills, capable of modeling complex engineering problems into executable AI Agent task structures

Preferred Qualifications

Experience with large model quantization techniques
Familiarity with mainstream inference acceleration or deployment frameworks
Knowledge of or experience in low-level kernel, operator, or performance optimization
Hands-on experience in deploying AI Agents for real-world tasks
Experience with complex engineering systems such as automated testing, benchmarking, CI, or performance analysis tools
Open-source contributions related to models, systems, compilers, acceleration, or Agent frameworks
Availability for an internship of at least 4 months, with on-site work 4 days per week or more

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.

ADDITIONAL INFORMATION: Intel is committed to Responsible Business Alliance (RBA) compliance and ethical hiring practices. We do not charge any fees during our hiring process. Candidates should never be required to pay recruitment fees, medical examination fees, or any other charges as a condition of employment. If you are asked to pay any fees during our hiring process, please report this immediately to your recruiter.

How we rate this

AI Software Engineer Intern at Intel rates 100 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Key facts

AI Software Engineer Intern is an open job at Intel.
Level rates this role AI Level 4 of 4: Builds AI.
The role is based in PRC, Shanghai.
The job was posted on October 20, 2026.
Seniority: intern.
Applications are handled by Intel. Apply on Intel

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

AI agentsDeep learningLLM InferencePerformance OptimizationPyTorchPython

Also common in software engineer jobs at this level

AWS C++Machine learning Kubernetes Java Generative AI

Pay

Typical software engineer job: $168k

This posting doesn't list pay. Use the typical software engineer figure when pay comes up. See software engineer jobs

Questions you could be asked

How do you decide when an AI agent can act on its own versus asking for approval first?
Tell me about a project where deep learning was part of your work. What did you do?
Tell me about a project where llm inference was part of your work. What did you do?
Tell me about a project where performance optimization was part of your work. What did you do?
Walk me through how you've used PyTorch in your day-to-day work.

Adapt your resume

List these exact terms on your resume: AI agents, Deep learning, LLM Inference, Performance Optimization, and PyTorch. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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