Data Processing Developer Technology Intern - 2027

AI in this role

Research and develop techniques to GPU accelerate AI and deep learning workloads on advanced hardware architectures.

cudaopenaccopenmpmpic

computer-visionnlpparallel-computingdeep-learningmachine-learninggpu-accelerationperformance-optimization

We’re currently seeking for an internship position in the Data Processing Developer Technology team. Would you enjoy researching parallel algorithms to accelerate AI and Data Processing workloads on advanced computer architectures? Do you find it rewarding to identify and eliminate system bottlenecks to achieve the best possible performance on pioneering computer hardware? Could you be thrilled about an opportunity to partner with the developer community, working at the forefront of technology breakthroughs that contribute to the success of an industry leader like NVIDIA? If so, we invite you to consider an internship with the Developer Technology Team.

What you will be doing:

In this position, you will research and develop techniques to GPU accelerate workloads in deep learning, machine learning or other AI domains.
Work directly with other technical experts in their fields (industry and academia) to perform in-depth analysis and optimization of complex AI and HPC algorithms to ensure optimal AI solutions on modern CPU and GPU architectures.
Publish and/or present discovered optimization techniques in developer blogs or relevant conferences to engage and educate the developer community.
Influence the design of next-generation hardware architectures, software, and programming models in collaboration with research, hardware, system software, libraries, and tools teams at NVIDIA.

What we need to see:

Currently pursuing a PhD or Master degree in Computer Science, Computer Engineering, or related computationally focused science degree.
Programming fluency in C/C++ with a deep understanding of algorithms and software development.
A background that includes parallel programming, e.g., CUDA, OpenACC, OpenMP, MPI, pthreads, etc.
Effective communication and organization skills, with a logical approach to problem solving, good time management, and prioritization skills.

Ways to stand out from the crowd:

Expertise in parallelization and performance optimization of Deep Learning models arising from Natural Language Processing, Computer Vision, Recommender Systems, etc.
Excellent understanding of linear algebra.

NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

Applications will be accepted until November 8, 2026.

Please note: We will be reviewing applications on a rolling basis as they are submitted. Strong candidates may be contacted for next steps before the application deadline. We encourage you to apply early.

How we rate this

Data Processing Developer Technology Intern - 2027 at NVIDIA rates 90 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

Data Processing Developer Technology Intern - 2027 is an open job at NVIDIA.
Level rates this role AI Level 4 of 4: Builds AI.
The role is based in Germany, Munich.
The job was posted on October 4, 2026.
Seniority: intern.
Applications are handled by NVIDIA. Apply on NVIDIA

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 VisionNLPParallel ComputingDeep LearningMachine LearningGPU AccelerationPerformance OptimizationCuda

Questions you could be asked

Walk me through a computer vision problem you solved, from raw data to a deployed model.
What NLP problem have you worked on, and how did you measure whether it actually worked?
Tell me about a project where parallel computing was part of your work. What did you do?
Tell me about a project where deep learning was part of your work. What did you do?
Tell me about a project where machine learning was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: Computer Vision, NLP, Parallel Computing, Deep Learning, and Machine Learning. 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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