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About the Role

Lead the integration of diverse AI models including VLA, Vision, and Multimodal architectures by utilizing a proprietary kernel programming language to ensure accuracy and performance while maintaining a developer-ready stack.

Responsibilities

• Design and implement efficient kernels on FuriosaAI’s kernel programming stack targeting Tensor Contract Processor architectures.
• Diagnose and optimize kernel performance using profiling tools and roofline analysis for RNGD-accelerated AI models.
• Develop and apply automated kernel generation and optimization for AI workloads.
• Build diagnostic tools and testbeds for robust kernel validation.
• Drive end-to-end programming enablement on RNGDs by creating reproducible guides and reference implementations.

Requirements

• BS in Computer Science, Artificial Intelligence, Electrical Engineering, or a related field.
• Experience in low-level systems programming targeting XPU architectures.
• Experience collaborating across engineering, research, and product teams.
• MS or PhD in Computer Science, Artificial Intelligence, Electrical Engineering, or a related field.
• Experience in optimizing high-performance kernels on AI accelerators for AI products.
• Understanding of XPU architecture and software-hardware co-optimization strategies.
• Experience in open-source or research projects on AI model architectures such as Diffusion, Mamba, and VLA.
• Experience in designing efficient deep learning architectures and developing algorithms for AI applications.

Skills

• Kernel programming
• vISA
• TCL
• Tensor Contract Processor architecture
• Performance profiling
• Roofline analysis
• Automated kernel generation
• XPU architecture
• Software-hardware co-optimization
• Deep learning architecture design

Education Level

• BS in Computer Science, Artificial Intelligence, Electrical Engineering, or a related field
• MS or PhD in Computer Science, Artificial Intelligence, Electrical Engineering, or a related field