Senior AI Infrastructure Tools Engineer
Sunnyvale, CA
Cerebras Systems
Cerebras is the go-to platform for fast and effortless AI training. Learn more at cerebras.ai.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
- The AI Infrastructure Tools Engineer will be responsible for driving tools effort required to provide high uptime and service availability of AI Infrastructure at Cerebras.
- Architect, design, and develop framework and tools for monitoring, operations, and maintenance of AI Infrastructure.
- Collaborate with Cluster Deployment, Network Operations, and Cluster Operations teams to understand their needs and ensure tools meet their requirements.
- Identify areas for improvement and implement new tools or technologies to enhance AI infrastructure efficiency, reliability, and security.
- Use AI to analyze data and identify trends, patterns, and anomalies.
- Develop User Interface (UI), reporting, analytics, visualizations, and dashboards consumable by engineers, leadership, and customers.
Skills And Qualifications
- Bachelor’s degree or higher in Electrical Engineering, Computer Engineering or Computer Science.
- 10+ years of experience designing and building infrastructure tools.
- Must be proficient in python development, and or Golang.
- Expertise with cloud platforms like AWS, Azure, or Google Cloud.
- Manage tooling infrastructure using code, enabling repeatable and consistent deployments.
- Experience with containerization (e.g., Docker) and orchestration (e.g., Kubernetes).
- Expertise in setting up and maintain monitoring and logging systems
- Experience with network monitoring and analytics tools like Prometheus, Grafana; and familiarity with GNMI, OpenConfig, OpenTelemetry, or New Relic.
- Experience building dashboards and analytics. Understanding of UX/UI design techniques.
- Excellent problem-solving and analytical skills.
- Strong communication and collaboration skills.
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.
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* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Architecture AWS Azure Computer Science Docker Engineering GCP Generative AI Golang Google Cloud GPU Grafana Kubernetes Machine Learning ML infrastructure Open Source Python Research Security UX
Perks/benefits: Career development Startup environment
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