Software Engineer, Kernel Programming
AI Summary
Lead integration of AI models using FuriosaAI's kernel programming language, designing and optimizing kernels for Tensor Contract Processor architectures.
About this role
About FuriosaAI
FuriosaAI builds high-performance, high-efficiency AI compute for the Inference Era. Founded in 2017 by veteran semiconductor and AI algorithm engineers, Furiosa operates globally with offices in Korea and Silicon Valley, along with a compiler-focused R&D lab in Lisbon.
Our vision is to make AI computing sustainable, enabling access to powerful AI for everyone on Earth. We solve the AI hardware energy and operational cost crisis at the architectural level, rather than through brute force, building the world's first truly AI-native compute platform to unlock the full potential of artificial intelligence for every enterprise.
About the Role
Lead the integration of diverse AI models including VLA, Vision, and Multimodal architectures by utilizing our kernel programming language to ensure both accuracy and performance while keeping the stack ready for developers to use.
Key Responsibilities
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Design and implement efficient kernels on FuriosaAI’s kernel programming stack (including vISA, TCL), targeting Tensor Contract Processor (TCP) architectures.
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Diagnose and optimize kernel performance with profiling tools and roofline analysis for each RNGD-accelerated AI model.
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Develop and apply automated kernel generation and optimization for AI workloads.
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Build diagnostic tools or testbeds for robust and reliable kernel validation.
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Drive end-to-end programming enablement on RNGDs, creating reproducible guides and reference implementations.
Minimum Qualifications
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BS in Computer Science, Artificial Intelligence, Electrical Engineering, or a related field.
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Experience in low-level systems programming targeting XPU (e.g., NPU, GPU) architectures.
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Experience collaborating across engineering, research, and product teams to align software development with product requirements.
Preferred Qualifications
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MS or PhD in Computer Science, Artificial Intelligence, Electrical Engineering, or a related field.
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Experience in optimizing high-performance kernels on AI accelerators (e.g., GPU, TPU) for AI products.
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Understanding of XPU architecture (computation patterns, data movement) and software-hardware co-optimization strategies.
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Experience in open-source or research projects on AI model architectures such as Diffusion, Mamba, and VLA.
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Experience in designing efficient deep learning architectures and developing algorithms for AI applications.
Why Join FuriosaAI
The defining bottleneck of the AI era is building the right hardware and software stack to run it at global scale. Furiosa is solving this challenge holistically from the ground up.
With our flagship chip, RNGD, in mass production today and our next-generation platform in development with Broadcom, we are proving that full-stack, tensor-native compute is the future of AI infrastructure. This is a pivotal moment to join our team, right as we accelerate our global expansion.
At Furiosa, you will:
Solve AI’s Most Urgent Challenge. Help build the high-performance, energy-efficient inference hardware and software required to fulfill the promise of advanced AI.
Pioneer Full-Stack Co-Design. Work with teams that are architecting solutions from silicon up through the compiler (featuring innovations like Tensor Contraction Language and Virtual ISA) and serving frameworks.
Ship Real-World Silicon, Software, and Solutions. Turn breakthrough technology into commercial deployment. RNGD is in mass production with TSMC and running live enterprise workloads for global leaders like LG AI Research and Samsung SDS.
Partner With the Industry's Best. Collaborate across an elite global ecosystem that includes TSMC, Broadcom, SK Hynix, and GUC.
Do Your Life’s Best Work. Join a brilliant, low-ego, mission-driven team in a high-trust environment that values autonomy, intellectual curiosity, and shared ambition.
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