Cerebras Systems
Artificial Intelligence • Hardware • Healthcare Insurance
Cerebras Systems is a pioneering company that focuses on developing advanced AI hardware, specifically the Cerebras Wafer Scale Engine, which delivers unparalleled performance in AI inference, outperforming traditional GPU setups. Their cutting-edge technology enables organizations like Mayo Clinic and AlphaSense to run state-of-the-art AI models with remarkable speed and efficiency. With flexible deployment options including cloud and on-premises solutions, Cerebras is transforming the landscape of AI capabilities for innovative teams across various industries.
201 - 500 employees
Founded 2016
🤖 Artificial Intelligence
🔧 Hardware
⚕️ Healthcare Insurance
Principal Engineer, AI Inference Reliability
Job not on LinkedIn
October 30
Cerebras Systems
Artificial Intelligence • Hardware • Healthcare Insurance
Cerebras Systems is a pioneering company that focuses on developing advanced AI hardware, specifically the Cerebras Wafer Scale Engine, which delivers unparalleled performance in AI inference, outperforming traditional GPU setups. Their cutting-edge technology enables organizations like Mayo Clinic and AlphaSense to run state-of-the-art AI models with remarkable speed and efficiency. With flexible deployment options including cloud and on-premises solutions, Cerebras is transforming the landscape of AI capabilities for innovative teams across various industries.
201 - 500 employees
Founded 2016
🤖 Artificial Intelligence
🔧 Hardware
⚕️ Healthcare Insurance
📋 Description
• Define and drive reliability strategy: establish SLOs and ensure alignment across engineering. • Design and implement reliability mechanisms: build and evolve systems for fault detection, graceful degradation, failover, throttling, and recovery across multiple regions and data centers. • Lead large-scale incident management: own postmortems, root-cause analysis, and prevention loops for reliability-related incidents. • Architect for reliability and observability: influence system design for redundancy, durability, and debuggability. • Develop reliability tooling: create internal tools and frameworks for chaos testing, load simulation, and distributed fault injection. • Collaborate broadly: work across software, infrastructure, and hardware teams to ensure reliability is embedded into every layer of our inference service. • Monitor and communicate reliability metrics: build dashboards and alerts that measure service health and provide actionable insights. • Mentor and influence: guide engineers and set best practices for designing, testing, and operating reliable large-scale systems.
🎯 Requirements
• Bachelor's or master's degree in computer science or related field. • 7+ years of experience in backend, infrastructure, or reliability engineering for large-scale distributed systems. • Strong programming skills in at least one popular backend programming language such as Python, C++, Go, or Rust. • Deep and hard-earned experience of reliability principles: SLO/SLI/SLA design, incident response, and postmortem culture. • Excellent communication and cross-functional leadership skills. • Bonus: prior experience building large-scale AI infrastructure systems.
🏖️ Benefits
• Health insurance • 401(k) matching • Flexible work hours • Paid time off • Professional development opportunities
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