
Senior SW Engineer and Linux Kernel + Virtualization Expert JB-310
עלתה ל-JOBTIME לפני 16 שעות· בתוקף עד 24 בנובמבר 2026
- מיקום
- כל הארץ
- היקף משרה
- משרה מלאה
- תפקיד
- מהנדס/ת תוכנה
תיאור המשרה
What will you be doing?
•Design and develop Linux kernel code related to virtual memory management and memory-tiering
• Research, design and innovate methods, algorithms and supporting data-structures for managing memory hierarchies in virtualization environments
• Participate in research to analyze AI-based applications’ performance, identify bottlenecks and optimize various decision-making mechanisms based on benchmarking results
• Collaborate with professional team members and various global teams around the world on a daily basis
• Challenged to think outside of the box and come up with creative ideas to deal with complex challenges within Linux kernel
Requirements
What do we want to see?
• Bachelor degree or higher in Computer Engineering / Computer Science or equivalent
• 5+ years of experience in software development in Linux environment
• 5+ years of experience in storage / memory tiering / caching or prefetching domains
• 5+ years of hands-on experience in Linux kernel development / hacking / research
• Proficiency in C / C++ programming language
• Proven experience in Linux kernel memory management sub-system
• Working in Linux kernel open-source environment
• Deep system understanding and capability to enhance existing code
• Open-minded team player with a can-do attitude
• Fast learner, highly organized and detail-oriented, able to work on multiple deadlines in a fast-paced atmosphere
Ways to stand out from the crowd:
• M.Sc. or Ph.D. degree with expertise in fields related to OS and virtualization technology
• Papers and/or proven innovation in virtualization, storage/memory tiering or caching domains
• 2+ years of experience in optimizing applications’ performance
• Proficiency in additional low-level programming languages
• Proficiency in high-level programming languages: Python
• Familiarity with Agentic-AI workloads, their characteristics and bottlenecks