NVIDIA 2026 Internships: Software Engineering

By submitting your resume, you’re expressing interest in one of our 2026 Software Engineering Internships. We’ll review resumes on an ongoing basis, and a recruiter may reach out if your experience fits one of our many internship opportunities. 

NVIDIA pioneered accelerated computing to tackle challenges no one else can solve. Our work in AI and digital twins is transforming the world's largest industries and profoundly impacting society — from gaming to robotics, self-driving cars to life-saving healthcare, climate change to virtual worlds where we can all connect and create. 

Our internships offer an excellent opportunity to expand your career and get hands on experience with one of our industry leading Software teams. We’re seeking strategic, ambitious, hard-working, and creative individuals who are passionate about helping us tackle challenges no one else can solve. 

Throughout the 12-week full-time internship, students will work on projects that have a measurable impact on our business. We’re looking for students pursuing Bachelor's, Master's, or PhD degree within a relevant or related field.  

Potential Internships in this field include:  

Development Tools 

• Debugging complex system-level issues using Jenkins  

• Course or internship experience related to the following areas could be required: Relational Databases, Linear Algebra & Numerical Methods, Operating Systems (memory/resource management), Scheduling and Process Control, Hardware Virtualization 

Cloud 

• Supporting overall architecture and design of our cloud storage infrastructure  

• Implementing and troubleshooting storage and data platform tools, automating storage infrastructure end-to-end 

• Course or internship experience related to the following areas could be required: Distributed Systems, Data Structures & Algorithms, Virtualization, Automation/Scripting, Container & Cluster Management, Debugging 

Tools Infrastructure 

• Building industry leading technology by proving workflows and infrastructure, alongside a team of experts in production software development and chip design methodologies 

• Enabling success for content running on the chip from application tracing and analysis to modeling, diagnostics, performance tuning, and debugging  

• Course or internship experience related to the following areas and technologies could be required: Unix/Shell Scripting, Linux, Java, JavaScript (including Node, React, Vue), C++, CUDA, OOP, Go, Python, Git, GitLab, Perforce, Kubernetes and Microservices, Schedulers (LSF, SLURM), Containers (Docker), Configuration Automation (Ansible) 

Machine Learning Operations 

• Deep Learning, GPU Computing, Accelerated Computing 

• Validation Frameworks for Deep Learning, Deep Learning Frameworks and Libraries (NumPy, SciPy, cuBLAS, cuDNN) 

• Data Preprocessing, Training Acceleration (CUDA, cuDNN, NCCL), Convolution Operations (cuDNN), Real-Time Inference (TensorRT)   

• Building Infrastructure for Back-End Analytics  

What we need to see:  

Must be actively enrolled in a university pursuing a Bachelor's, Master's, or PhD degree in Electrical Engineering, Com