Data Processing Developer Intern

NVIDIA

. Research and develop techniques to GPU accelerate workloads in deep learning, machine learning or other AI domains .

Posted 10/4/2026internshipMunich • GermanyEntry LevelWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in GPU acceleration techniques for deep learning and machine learning, with a strong foundation in parallel programming and performance optimization. Engages effectively with the developer community and contributes to the advancement of next-generation hardware and software architectures.

Highest-signal resume keywords

PhD Or Master Degree In Computer ScienceProgramming Fluency In C/C++Parallel Programming Expertise (CUDA, OpenACC, OpenMP, MPI)Performance Optimization Of Deep Learning ModelsStrong Communication And Organization Skills

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

GPU Acceleration TechniquesDeep Learning OptimizationParallel ProgrammingAlgorithms DevelopmentPerformance OptimizationLinear AlgebraNatural Language ProcessingComputer VisionRecommender Systems

Soft Skills

Effective CommunicationLogical Problem SolvingTime ManagementPrioritization

Industry Keywords

AI DomainsHPC AlgorithmsDeveloper Community EngagementNext-Generation Hardware ArchitecturesSoftware Programming Models

Tech Stack

Tools & technologies

C++

About the role

Key responsibilities & impact

Research and develop techniques to GPU accelerate workloads in deep learning, machine learning or other AI domains
Work directly with technical experts from industry and academia to perform in-depth analysis and optimization of complex AI and HPC algorithms
Ensure optimal AI solutions on modern CPU and GPU architectures
Publish and/or present discovered optimization techniques in developer blogs or relevant conferences
Engage and educate the developer community
Influence the design of next-generation hardware architectures, software, and programming models
Collaborate with research, hardware, system software, libraries, and tools teams at NVIDIA

Requirements

What you’ll need

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
Background in parallel programming, e.g., CUDA, OpenACC, OpenMP, MPI, pthreads, etc.
Effective communication and organization skills
Logical approach to problem solving
Good time management and prioritization skills
Expertise in parallelization and performance optimization of Deep Learning models arising from Natural Language Processing, Computer Vision, Recommender Systems, etc. (ways to stand out)
Excellent understanding of linear algebra (ways to stand out)

Benefits

Comp & perks

Internship opportunity with NVIDIA
Opportunity to partner with the developer community
Opportunity to publish and/or present optimization techniques in developer blogs or relevant conferences
Opportunity to influence next-generation hardware architectures, software, and programming models