below marketmost similar roles pay hereabove market
This listing doesn't post a salary. Most similar roles pay
$118,621–$235,750.
Based on 240 similar postings.
Employer
About Nvidia
Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing
Nvidia currently has
1623 open roles
on FindRole.
Listed pay typically runs
$184,000–$287,500
across 1110 roles with salary data.
NVIDIA 2027 Summer Internships: Ph.D. Engineering offers a research-focused internship within the Computer Architecture and Systems teams. Interns will design and implement novel ideas in GPU and CPU architectures, operating systems, AI systems, and distributed systems to advance computing, graphics, and media processing. Key responsibilities include collaborating with internal teams and external researchers to transfer research into products, resulting in prototypes, patents, or original research publications. Candidates should possess programming skills in C, C++, Python, and CUDA, along with a strong research background. Specific technical domains include chip-level and system-level architecture, scalable memory systems, interconnects, hardware-software co-design, and high-performance networking. The work addresses technical challenges in large-scale systems, including power efficiency, LLM training infrastructure, and optimizing GPU-accelerated workloads for AI and crypto algorithms.
Design and implement novel ideas in GPU/CPU architectures, operating systems, and distributed systems.
Develop technologies for graphics, media processing, and other core business areas.
Translate research findings into practical products or new product types for production teams.
Produce tangible deliverables including prototypes, patents, and published original research.
Optimize performance, power, and energy efficiency in large-scale computing systems.
Develop hardware-software co-designs specifically for AI/ML workloads and infrastructure.
Create and optimize GPU-accelerated algorithms and parallel computing programming models.
Design high-performance networking solutions including topologies, routing, and congestion control.
What we're looking for
Must be actively enrolled in a university pursuing a Ph.D. degree in Computer Science, Electrical Engineering, or a related field.
Must provide an anticipated graduation date (month and year) on the resume or CV.
Proficiency in programming languages and technologies including C, C++, Python, and CUDA.
Strong background in research with publications at top conferences.
Excellent communication and collaboration skills.
Research experience in at least one area such as GPU/CPU architecture, AI systems, distributed systems, or high-performance networking (depending on the internship).
VLSI
Physical Design
Floorplanning
Place and Route
Static Timing Analysis
Clock Tree Synthesis
Physical Verification
DRC
LVS
Power Integrity
IR Drop Analysis
RC Extraction
Digital Design
Mixed-Signal Design
Computer Architecture
ICC2
PrimeTime
dc_shell
Innovus
SeaHawk
Python
C++
C
Perl
TCL
Linux
SKILL
Make
Design Compiler
Scheme
Python
C++
CUDA
PyTorch
JAX
TensorFlow
Deep Learning
Generative AI
Computer Vision
Large Language Models
Diffusion Models
Multimodal Foundation Models
Action-Based Transformers
Physics-Based Simulation
Synthetic Data Generation
Verilog
SystemVerilog
VHDL
Python
Perl
SPICE
HSPICE
CMOS
FinFET
Cadence
Synopsys
EDA Tools
Digital Circuit Design
SRAM
Timing and Delay Analysis
Power Management
Monte Carlo
SerDes
Object-Oriented Programming
Operating Systems