Research Scientist Intern - Graphics, ML

AI in this role

pytorch

computer-visionai-research

Job Details:

Job Description:

The Graphics Research Organization at Intel is seeking a highly motivated Research Scientist Intern to join its world-class team. This role offers an opportunity to help shape next-generation graphics technologies and experiences by conducting cutting-edge research in real-time 3D rendering, machine learning, and highly parallel algorithms.

As an intern, you will collaborate with industry-leading researchers to develop innovative graphics and AI techniques. Your work may contribute directly to Intel's graphics hardware and software products while advancing the state of the art in both industry and academia through research publications.

We are looking for curious, collaborative, and technically strong candidates who are passionate about graphics research, possess excellent communication skills, and are eager to explore new ideas that drive innovation.

Qualifications:

Minimum Qualifications

Currently pursuing a PhD in Computer Science, Electrical Engineering, or a related field with a focus on computer graphics and machine learning.

At least 1 year of academic, research, or industry experience in:

- Modern C/C++ and Python programming.

- Machine learning concepts, algorithms, and frameworks such as PyTorch.

- Advanced graphics techniques including rasterization, ray tracing, physically based rendering, light transport, sampling strategies, acceleration structures, level of detail, shading, appearance modeling, and Monte Carlo methods.

- Graphics APIs such as OpenGL, Vulkan, or DirectX, and/or shading languages including GLSL and HLSL.

- GPGPU programming technologies such as CUDA, SYCL, or OpenCL.

Preferred Qualifications

Publications in top-tier computer graphics, computer vision conferences, or journals.

Strong foundation in linear algebra, numerical optimization, probability, and statistical estimation.

Experience with image processing and computer vision techniques, including multi-scale filtering, Fourier transforms, optical flow, feature alignment, and image segmentation.

Familiarity with vision transformer models such as DINO, CLIP, and V-JEPA.

Experience developing neural rendering applications, including super-resolution, denoising, and deblurring.

Research or software engineering experience through internships, industry roles, open-source contributions, or competitive programming.

Experience applying machine learning techniques to real-time graphics problems.

Understanding of GPU architectures, graphics workloads, and performance optimization.

Experience with profiling, debugging, and performance analysis tools.

This internship is ideal for PhD students who want to push the boundaries of graphics and AI research while contributing to technologies that impact millions of users worldwide.

Job Type:

Student / Intern

Shift:

Shift 1 (United States of America)

Primary Location:

Virtual US

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

Benefits

We offer a total compensation package that ranks among the best in the industry. It consists of competitive pay, stock bonuses, and benefit programs which include health, retirement, and vacation. Find out more about the benefits of working at Intel.

Annual Salary Range for jobs which could be performed in the US: $170,598.00-170,602.00 USD

The range displayed on this job posting reflects the minimum and maximum target compensation for the position across all US locations. Our standard internship rates are based on your degree, location, and the job role. Your recruiter can share more about the specific compensation range for your preferred location and job role during the hiring process.

Work Model for this Role

This role is available as a fully home-based and generally would require you to attend Intel sites only occasionally based on business need. However, you must live and work from the country specified in the job posting, in which Intel has a legal presence. Due to legal regulations, remote work from any other country is unfortunately not permitted. * Job posting details (such as work model, location or time type) are subject to change.The application window for this job posting is expected to end by 12/30/2027

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

Research Scientist Intern - Graphics, ML at Intel rates 95 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.

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

Computer VisionAI ResearchPyTorch

Questions you could be asked

Walk me through a computer vision problem you solved, from raw data to a deployed model.
Tell me about a research question you investigated. What did you find?
What are the limits of PyTorch that you've run into, and how did you work around them?
How would you decide a model or AI system is ready to ship?
Tell me about a time a model underperformed in production. How did you find out, and what did you change?

Adapt your resume

List these exact terms on your resume: Computer Vision, AI Research, 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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