Principal Engineer - GPU & CUDA Programming

Role Overview

The Principal Engineer in GPU & CUDA Programming will lead the design and optimization of GPU-accelerated computing technologies at Synopsys, driving innovation in chip design and semiconductor software solutions.

About the Company

Synopsys is a leader in electronic design automation, specializing in software and IP solutions that lead innovations in the chip design, verification, and manufacturing process.

Experience Level

The position requires a minimum of 10 years of experience in software engineering, particularly in GPU computing and algorithm design.

Key Responsibilities

• Optimize existing GPU implementations for ILT (Inverse Lithography Technology) software.
• Design and develop new algorithms to manage large-scale geometric datasets.
• Collaborate with cross-functional teams for integrating GPU features into solutions.
• Lead performance testing and benchmarking to enhance GPU algorithm throughput.
• Conduct research on GPU technology advancements for product integration.
• Engage with customers and hardware vendors to ensure effective solutions.

Required Skills and Experience

• Advanced knowledge of CUDA or similar technologies for GPU computing.
• Proficient in programming languages including C/C++ and Python.
• Strong understanding of algorithms and data structures with a focus on performance optimization.
• Experience in computational geometry, specifically algorithms like Beziers, NURBS, and B-splines.
• Knowledge in Optical Proximity Correction and Inverse Lithography Technology is a plus.

Education Requirements

A Bachelor’s, Master’s, or Ph.D. in Computer Science or a related field is required.