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

📅 Jul 16
Software Test AutomationDistributed SystemsAI Cluster InfrastructureDatacenter Networking
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📜 Description

  • Define test strategies and methodologies for cutting-edge AI infrastructure.
  • Break distributed ML training and inference systems into components that can be unit tested.
  • Automate tests for cluster availability, failure scenarios, performance, stress, and security.
  • Validate cluster software, hardware, networking, and security features across large deployments.
  • Qualify high-speed switches, routers, optics, and other cluster networking solutions.
  • Champion cluster reliability, security, uptime, and observability.

🛠️ Requirements

  • Bachelor's or master's degree in engineering, computer science, electrical engineering, AI, data science, or a related field.
  • 10+ years of experience testing enterprise software, distributed systems, datacenter hardware, or datacenter software.
  • Experience with enterprise or cloud networking infrastructure, high-speed switches, routers, and firewalls.
  • Experience qualifying Juniper, Arista, or Cisco platforms and Ixia or Spirent network test equipment.
  • Knowledge of datacenter technologies such as BGP, ECN, and PFC, and experience testing network security, compliance, and firewalls.
  • Strong coding skills in Python, Go, or C/C++, plus debugging skills for distributed systems, hardware, and software.
  • Understanding of operating system internals, datacenter layouts, and device performance across PCIe, networking, and storage.
  • Experience with AWS, Kubernetes, and Docker; ML training and inference or hardware accelerator experience is a 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.
  • Our simple, non-corporate work culture that respects individual beliefs.
Full job description

Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.

This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.

Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.

In AI infrastructure organization, simplifying large hardware deployments with push button, single pane of glass for observability/monitoring and software capabilities for build-in resiliency are some of the key focus areas. As senior software development engineer in Test, we are looking for a candidate who can make a big impact on how we test and validate thousands of nodes in large deployments to ensure the cluster is 99.999% reliable.


Responsibities:

  • You will be hired to innovate and execute tests on cutting edge AI infrastructure. Be a thinker, define optimized test strategies and methodologies.

  • Cerebras is growing and innovating at a rapid pace and so is the ML community and AI models. Be a quick learner, adapt to new technologies, and bring your expertise. We are looking to hire a team with a diverse skill set.

  • Deep understanding of how large-scale distributed ML training and inference works. Build a strong understanding of how to break these large distributed systems challenge into smaller components that can be unit tested

  • Automate first approach - In large scale deployment, automation drives efficiency and scalability. Aim for 100% automated tests to test all cluster features in areas of high availability, failure scenarios, performance, stress and security

  • Champion cluster security, reliability for uptime of 99.9999% and ease of use with observability.

  • Test all components of AI cluster including but not limited to cluster software involving kubernetes, prometheus and grafana. Cluster hardware components like ML wafer scale accelerators, CPU runtime nodes, High speed swarmx interconnect, High speed data transfer of weights through memoryx interconnect

  • Qualify cluster networking solutions which consists of high-speed switches, routers and optics from various vendors

  • Qualify cluster security features including OS security, network security, cloud compliance user access and security certifications

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. 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

Why Join Cerebras

People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:

  1. Build a breakthrough AI platform beyond the constraints of the GPU.

  2. Publish and open source their cutting-edge AI research.

  3. Work on one of the fastest AI supercomputers in the world.

  4. Enjoy job stability with startup vitality.

  5. Our simple, non-corporate work culture that respects individual beliefs.

Find out more about what it's like to work at Cerebras here!

Apply today and become part of the forefront of groundbreaking advancements in AI!

Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.

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