Systems Software Engineer - New College Grad 2026

NVIDIA AI; Hillsboro (OR); On-site; USD 140,000 - 200,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

NVIDIA AI is seeking a highly skilled researcher to develop advanced computational methods for semiconductor manufacturing and design. You will leverage GPU acceleration and CUDA to create scalable, distributed software solutions that accelerate yield and time to market.

Candidates should have an MS or PhD in CS/EE with strong AI/ML expertise, plus proven experience in parallel programming and low-level performance optimization to push the boundaries of semiconductor software.

Qualifications

• MS or PhD in Computer Science or Computer Engineering with experience in complex software for semiconductor fabrication.
• Proficiency in AI/ML techniques, low-level performance optimization, and parallel programming.

Responsibilities

• Develop advanced computational methods for semiconductor manufacturing and design to accelerate yield and time to market.
• Utilize GPU acceleration and CUDA to implement scalable, distributed software solutions.

Skills

Distributed Computing

Computational Geometry

Diffractive Optics

Artificial Intelligence

CUDA

Low-level Performance Optimization

Memory Management

Cache Compression

Work-load Balancing

Deep Learning

Algorithm Development

Data Structures

Computational Theory

Parallel Programming

Model Optimization

Semiconductor Design

Education

MS/PhD in Computer Science or Computer Engineering

Tools

CUDA

Job description

Develop advanced computational methods for semiconductor manufacturing and design to accelerate yield and time to market. Utilize GPU acceleration and CUDA to implement scalable, distributed software solutions.

Requirements:

Requires a MS or PhD in Computer Science or Computer Engineering with experience in complex software for semiconductor fabrication. Candidates must demonstrate proficiency in AI/ML techniques, low-level performance optimization, and parallel programming.

Key Skills:

• Distributed Computing
• Computational Geometry
• Diffractive Optics
• Artificial Intelligence
• CUDA
• Low-level Performance Optimization
• Memory Management
• Cache Compression
• Work-load Balancing
• Deep Learning
• Algorithm Development
• Data Structures
• Computational Theory
• Parallel Programming
• Model Optimization
• Semiconductor Design

Benefits:

• Equity
• Benefits