NextSilicon is reimagining high-performance computing (HPC & AI). Our accelerated compute solutions leverage intelligent adaptive algorithms to vastly accelerate supercomputers, driving them forward into a new generation. We have developed a novel software-defined hardware architecture that is achieving significant advancements in both the HPC and AI domains.
At NextSilicon, everything we do is guided by three core values:
- Professionalism: We get exceptional results through professionalism and unwavering dedication to quality and performance.
- Unity: Collaboration is key to success; we foster a work environment where every employee feels valued and heard.
- Impact: We're passionate about developing technologies that make a meaningful impact on industries, communities, and individuals worldwide.
The AI software team is building solutions that enable the latest AI models and workflows to run efficiently on NextSilicon’s unique hardware architecture—unlocking a new level of performance.
We are seeking a talented engineer to work on our AI software stack—specifically, the low-level optimization of AI models and kernels for our unique hardware architecture.
Requirements- B.Sc. degree in software engineering, computer science, or a related field.
- 5+ years of experience in C/C++ programming with a focus on performance-critical, distributed, or resource-constrained systems.
- Proficiency in writing AI kernels for GPUs such as GEMM and FlashAttention, and in low level software/firmware implementations
- Good understanding of HW/SW interfaces, memory management, SIMD/vectorization
- Excellent communication and teamwork skills
- Strong problem-solving skills and the ability to analyze and debug complex issues.
- Experience with ML accelerators and AI compilers - a plus.
- Develop our optimized AI libraries and related components in the SW stack.
- Drive the performance optimization of AI models running on our unique architecture.
What We Do
We believe in a smarter future and want to create new opportunities for innovation. In order to achieve this, we’re rethinking compute architectures for the future of computer processing.
