Senior Computer Engineer

Company Description: UnifabriX develops advanced Memory over Fabrics solutions that optimize GPU and AI cloud infrastructures, as well as high-performance computing (HPC) environments. The company builds on open, standards-based architectures such as CXL and UALink, enabling seamless scalability across complex systems. Its technology is designed for ultra-low latency and high-bandwidth memory access, supporting demanding next-generation AI workloads. Candidates joining UnifabriX will contribute to cutting-edge infrastructure solutions at the intersection of AI, Cloud, and HPC.

Role Description: The Senior Computer Engineer will design, implement, and optimize hardware–software solutions that leverage Memory over Fabrics technologies for GPU, AI, and HPC platforms. Day-to-day responsibilities include developing and validating system architectures, collaborating with software and hardware teams on development, performance optimization, and troubleshooting complex issues across compute, memory, and networking layers. The role involves contributing to external and internal tools, participating in design reviews, ensuring security and reliability of deployed solutions, and documenting technical designs and best practices. This is a full-time, on-site role located in Haifa, requiring close collaboration with cross-functional engineering teams.

Qualifications

• Bachelor’s or Master’s degree in Computer Engineering, Computer Science, Electrical Engineering, or a related technical field.
• Strong foundation in Computer Engineering and Computer Science, with experience in system architecture and low-level system design.
• Minimum 8 years of experience with a low-level programming language (C, C++, Rust, or similar) 
• Ability to work in remote Linux environments over the command line (SSH, bash, terminal) 
• Experience writing kernel code is an advantage
• Understanding of PCIe / CXL and memory protocols (DDR)
• Demonstrated ability in troubleshooting complex hardware–software interactions, system integration issues, and performance bottlenecks.
• Experience with GPU computing, AI workloads, HPC clusters, or memory fabric technologies (e.g., CXL, UALink) is highly beneficial.
• Strong analytical, communication, and collaboration skills, with the ability to work effectively in a multidisciplinary engineering environment.