Senior Software Development Engineer in Test – AI Cluster Senior Software Development Engineer in Test – AI Cluster Get AI-powered advice on this job and more exclusive features. Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. Our novel wafer-scale architecture provides the AI compute power of dozens of GPUs on a single chip, with the programming simplicity of a single device. This approach allows Cerebras to deliver industry-leading training and inference speeds and empowers machine learning users to effortlessly run large-scale ML applications, without the hassle of managing hundreds of GPUs or TPUs. Cerebras' current customers include global corporations across multiple industries, national labs, and top-tier healthcare systems. In January, we announced a multi-year, multi-million-dollar partnership with Mayo Clinic, underscoring our commitment to transforming AI applications across various fields. In August, we launched Cerebras Inference, the fastest Generative AI inference solution in the world, over 10 times faster than GPU-based hyperscale cloud inference services. Responsibilities 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 memory interconnect. Skills And Qualifications Bachelor's or master's degree in engineering in computer science, electrical, AI, data science or related field 5+ years of experience in testing one of areas like enterprise software, distributed systems, datacenter hardware and software Strong coding skills in one of the programming languages like python, golang and C/C++ Strong debugging skills to debug issues in large distributed systems, hardware, and software. Experience with debugging tools like pdb, gdb, strace and network monitors Strong understanding of operating systems internals like memory management, file system working, security and performance Strong understanding of datacenter layout, device performance characteristics like Servers, Memory, BIOS, 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 Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. Our novel wafer-scale architecture provides the AI compute power of dozens of GPUs on a single chip, with the programming simplicity of a single device. This approach allows Cerebras to deliver industry-leading training and inference speeds and empowers machine learning users to effortlessly run large-scale ML applications, without the hassle of managing hundreds of GPUs or TPUs.

Cerebras' current customers include global corporations across multiple industries, national labs, and top-tier healthcare systems. In January, we announced a multi-year, multi-million-dollar partnership with Mayo Clinic, underscoring our commitment to transforming AI applications across various fields. In August, we launched Cerebras Inference, the fastest Generative AI inference solution in the world, over 10 times faster than GPU-based hyperscale cloud inference services. Responsibilities

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 memory interconnect.

Skills And Qualifications

Bachelor's or master's degree in engineering in computer science, electrical, AI, data science or related field

5+ years of experience in testing one of areas like enterprise software, distributed systems, datacenter hardware and software

Strong coding skills in one of the programming languages like python, golang and C/C++

Strong debugging skills to debug issues in large distributed systems, hardware, and software. Experience with debugging tools like pdb, gdb, strace and network monitors

Strong understanding of operating systems internals like memory management, file system working, security and performance

Strong understanding of datacenter layout, device performance characteristics like Servers, Memory, BIOS, 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:

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.

Read our blog:Five Reasons to Join Cerebras in 2025.

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.

This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice. Seniority level Seniority level Mid-Senior level Employment type Employment type Full-time Job function Job function Engineering and Information Technology Referrals increase your chances of interviewing at Cerebras Systems by 2x Get notified about new Senior Software Engineer jobs in Sunnyvale, CA . San Jose, CA $153,600.00-$286,600.00 2 minutes ago San Jose, CA $133,900.00-$242,000.00 2 minutes ago Senior Developer Events Manager, Google Cloud Sunnyvale, CA $165,000.00-$245,000.00 5 days ago Principal Software Engineer - Computational Chemistry / Molecular Dynamics San Mateo, CA $90,000.00-$150,000.00 1 year ago San Jose, CA $153,600.00-$286,600.00 2 minutes ago Software Engineering Technical Leader (Control Plane) --Cisco Hypershield San Jose, CA $163,900.00-$305,100.00 4 days ago San Jose, CA $153,600.00-$286,600.00 2 minutes ago San Jose, CA $153,600.00-$286,600.00 2 minutes ago San Jose, CA $163,360.00-$245,040.00 21 hours ago San Jose, CA $153,600.00-$286,600.00 2 minutes ago Senior System Software Engineer, Power and Thermal Management Senior / Staff Software Engineer - Computational Chemistry / Molecular Dynamics Senior Controls Engineer, Core Development Mountain View, CA $183,825.00-$275,975.00 20 hours ago San Jose, CA $133,900.00-$242,000.00 2 minutes ago Tech Lead Software Engineer, TikTok AI Video Editing San Jose, CA $224,000.00-$410,000.00 3 days ago Santa Clara, CA $163,008.00-$254,700.00 5 hours ago Sunnyvale, CA $143,000.00-$286,000.00 5 days ago San Jose, CA $133,900.00-$242,000.00 2 minutes ago San Jose, CA $153,600.00-$286,600.00 2 minutes ago San Francisco Bay Area $215,000.00-$295,000.00 2 weeks ago San Jose, CA $133,900.00-$242,000.00 2 minutes ago Sunnyvale, CA $248,000.00-$349,000.00 5 days ago Senior Software Development Engineer, Virtual Network San Jose, CA $194,000.00-$410,000.00 3 weeks ago San Mateo, CA $448,990.00-$515,210.00 2 weeks ago Mountain View, CA $204,000.00-$259,000.00 2 weeks ago Sr. Software Engineer, Plant Modeling and Tools Sr Principal Engineer Software (AIOps for NGFW) Sr. Software Engineer, Supply Chain Applications We’re unlocking community knowledge in a new way. Experts add insights directly into each article, started with the help of AI.

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