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Parallel Compute Frameworks Engineer
SiFive is an idea-to-silicon company founded by the inventors of RISC-V to simplify the design and production of custom SoCs.
As the leading commercial provider of RISC-V processor IP, SiFive is on a mission to help engineers design custom chips for domain-specific solutions for many markets, including 5G, edge AI, enterprise networking, storage, and consumer devices.
Industry-leading innovators, including six of the top ten semiconductor companies, are working with SiFive thanks to our proven success, deep expertise, and rich partner ecosystem. With SiFive’s rich IP ecosystem and accessible design platform, every market has access to the development of workload-focused hardware needed to design next-generation products.
SiFive was founded and is actively run by the developers of RISC-V. If you are passionate about working with industry leaders and innovators, then send us your application today!
At SiFive, we build a culture of hardware-software codesign to develop a highly optimized hardware and software IP that targets a wide range of applications and domains; our goal is to optimize the hardware and software solutions while keeping modularity and reuse. We are building the next generation technology in compute and parallel computing solutions. The framework engineer charter is to integrate SiFive software and hardware solutions into application frameworks and optimize the end-to-end performance and quality of these frameworks on SiFive solutions while leveraging the open-source software and hardware RISC-V echo system and contributing to it.
- AI/ML or Heterogeneous computing infrastructure development
- Parallel programming & optimization
- Deep learning application/middleware integration
- Open-source software development/ integration
- Co-work with SW & HW members for performance exploring and tuning
- 3+ years Large Scale Software design and programming experience in C/C++/Python for development, debugging, testing and performance analysis
- Strong C/C++ programming
- Basic understanding of Deep Learning
- Familiarity with AI Compiler (like MLIR/TVM/Glow etc) is plus
- Open source upstreaming experience is plus