Senior Software Development Engineer in Test (SDET) - AI Cluster Networking and Security

The role

The candidate will innovate and execute tests on cutting edge AI infrastructure. They will define test strategies to validate thousands of nodes in large deployments to ensure cluster reliability.

What you will do

• Innovate and execute tests on cutting edge AI infrastructure
• Define optimized test strategies and methodologies
• Build understanding of how to break large distributed systems into unit testable components
• Aim for 100% automated tests for cluster features including high availability, failure scenarios, performance, stress and security
• Champion cluster security, reliability and ease of use with observability
• Test cluster software involving kubernetes, prometheus and grafana
• Test cluster hardware components like ML wafer scale accelerators, CPU runtime nodes, High speed swarmx interconnect, and High speed data transfer of weights through memoryx interconnect
• Qualify cluster networking solutions including high-speed switches, routers and optics
• Qualify cluster security features including OS security, network security, cloud compliance user access and security certifications

Required qualifications

• Bachelor's or master's degree in engineering in computer science, electrical, AI, data science of related field
• 10+ years of experience in testing one of areas like enterprise software, distributed systems, datacenter hardware and software
• Experience working in large enterprise or cloud networking infrastructure, high speed switches, routers, firewalls
• Experience in qualifying networking vendor platforms like Juniper, Arista or Cisco and network test equipment like Ixia/Spirent
• Experience in Datacenter technology like BGP, ECN, PFC
• Experience testing networking security, compliance and firewalls
• Strong coding skills in one of the programming languages like python, golang or C/C++
• Strong debugging skills to debug issues in large distributed systems, hardware, and software
• Experience with debugging tools like gdb, strace, networking monitors
• Strong understanding of operating systems internals like memory management, file system working, security basics and performance
• Strong understanding of datacenter layout, device performance characteristics like PCIe, networking and storage
• Experience with cloud technologies like AWS, kubernetes and dockers

Nice to have

• Monitoring tools like grafana, prometheus is huge plus
• Understanding and experience of ML model training and inference is a huge plus
• Understand of ML hardware accelerators like GPU, custom accelerator ASIC is a huge plus

Benefits

• Build a breakthrough AI platform beyond the constraints of the GPU
• Publish and open source their cutting-edge AI research
• Work on one of the fastest AI supercomputers in the world
• Enjoy job stability with startup vitality
• Simple, non-corporate work culture that respects individual beliefs

About the company

Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. The company works with leading model labs, global enterprises, and cutting-edge AI-native startups.