AI Frameworks Intern

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AI Frameworks Intern

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locations

Poland, Gdansk

time type

Part time

posted on

Posted Today

job requisition id

JR0287895

Job Details:

Job Description:

Join Intel's PyTorch enablement team as an intern and help bring Intel datacenter and integrated GPU acceleration to one of the world's most widely used deep learning frameworks.

You will work alongside experienced engineers on PyTorch and PyTorch ecosystem open-source projects such as torch-xpu-ops, gaining real hands-on experience in deep learning and machine learning framework internals, GPU compute software stacks, and platform engineering - with your code shipping in a project used by millions of developers worldwide.

Your responsibilities will include:

• Implementing, debugging, and testing PyTorch operators/kernels for the Intel GPU (XPU) backend - primarily in Python, C++ with some SYCL
• Investigating and fixing OS-specific builds, tests, and runtime issues in PyTorch and ecosystem projects such as torch-xpu-ops
• Writing and maintaining unit tests; triaging and root-causing CI failures
• Collaborating directly with the upstream open-source PyTorch community (GitHub PRs, code reviews, design discussions)
• Documenting findings and contributing to the team's internal knowledge base

Qualifications:

Minimum Qualifications

• Currently pursuing a Bachelor's or Master's degree in Computer Science, Software Engineering, or a related field; completion of at least the first two years of study is preferred
• Solid knowledge and hands-on writing experience in Python
• Basic working knowledge of C/C++
• Familiarity with machine learning and deep learning concepts, backed up with personal passion
• Experience using AI/ML frameworks such as PyTorch, TensorFlow, JAX, or similar
• Knowledge of Git and collaborative software development practices
• Able to make best use of AI assistance for software development, including agentic AI tools and frameworks (e.g., Microsoft Copilot, Claude Code, OpenCode)
• Strong analytical and debugging mindset

Preferred Qualifications

• Hands-on experience developing AI/ML projects through coursework, research, hackathons, internships, or open-source contributions
• Knowledge/exposure to GPU programming concepts (CUDA, SYCL, OpenCL)
• Experience developing/debugging on Linux and Windows
• Any prior open-source contribution (GitHub PRs, issue triage)
• Familiarity with CI/CD tooling (Jenkins, GitHub Actions)

We invite you to explore this opportunity to grow your skills, collaborate with innovative teams, and contribute to impactful projects in a supportive and dynamic environment. Apply now to begin your journey with Intel.

Job Type:

Student / Intern

Shift:

Shift 1 (Poland)

Primary Location:

Poland, Gdansk

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.

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Position of Trust

N/A

EU Salary

We offer a total compensation package that ranks among the best in the industry.

The minimum Annual Salary for this job which could be performed in Poland is: 68 880,00 zł

The job posting reflects the minimum base compensation for this role. Our standard internship rates are aligned with the specific job role and degree level. As part of our total compensation approach, the final offer may also include additional pay components and benefits. Your recruiting team will provide the confirmed base salary along with any applicable total compensation elements upon employment offer delivery.

Work Model for this Role

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. * Job posting details (such as work model, location or time type) are subject to change.

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