GPU/HPC R&D Principal Engineer

At Synopsys, we drive the innovations that shape the way we live and connect. Our technology is central to the Era of Pervasive Intelligence, from self-driving cars to learning machines. We lead in chip design, verification, and IP integration, empowering the creation of high-performance silicon chips and software content. Join us to transform the future through continuous technological innovation.

You are an experienced and passionate GPU R&D Engineer with a strong background in optimizing and implementing GPU-accelerated algorithms. You have a deep understanding of CUDA or similar technologies, and you excel in performance improvements and integration with existing tools. Your expertise in algorithms and data structures, combined with your collaborative skills, make you a valuable asset to any team. You are always eager to stay current on GPU technology trends and incorporate the latest advancements into your work. With at least 8 years of experience, you are ready to take on challenging projects and deliver optimal solutions rapidly, contributing to the fast-paced environment at Synopsys.

• Optimize existing GPU implementations for ILT software.
• Design new GPU-accelerated algorithms for large-scale geometric data handling for ILT.
• Collaborate with cross-functional teams to ensure seamless integration of GPU features.
• Lead benchmarking and performance testing initiatives.
• Stay current on GPU technology trends and design the latest advancements into the system.
• Work closely with customers and hardware vendors to deliver optimal solutions swiftly.

• Enhance the performance and efficiency of ILT software through optimized GPU implementations.
• Drive innovation in GPU-accelerated algorithms for complex geometric data handling.
• Ensure the seamless integration of GPU features within existing Mask Synthesis tools.
• Lead initiatives that set new benchmarks for performance and reliability.
• Keep Synopsys at the forefront of GPU technology advancements.
• Accelerate the manufacturing of new chips by delivering rapid and optimal solutions.

• Bachelors, Masters, or Ph.D. in Computer Science or a related field.
• At least 8 years of experience in GPU optimization and implementation.
• Advanced knowledge of CUDA or similar technologies.
• Proficiency in C/C++, Python, and distributed computing environments.
• Strong understanding of algorithms and data structures.

• Exceptional troubleshooting and collaborative skills.
• Passionate about staying up-to-date with the latest GPU technology trends.
• Detail-oriented and committed to delivering high-quality solutions.
• Strong communicator with the ability to work effectively in cross-functional teams.
• Innovative thinker who thrives in a fast-paced, dynamic environment.

You will be part of a dedicated team of engineers focused on developing and optimizing ILT software. The team collaborates closely with customers, hardware vendors, and cross-functional groups within Synopsys to ensure the delivery of cutting-edge solutions. Together, we strive to push the boundaries of what is possible in the EDA industry.

We offer a comprehensive range of health, wellness, and financial benefits to cater to your needs. Our total rewards include both monetary and non-monetary offerings. Your recruiter will provide more details about the salary range and benefits during the hiring process.

At Synopsys, we want talented people of every background to feel valued and supported to do their best work. Synopsys considers all applicants for employment without regard to race, color, religion, national origin, gender, sexual orientation, age, military veteran status, or disability.

• Email


• LinkedIn


• X


• Facebook