Kernel Reliability Software Engineer

Engg; United States; On-site; USD 140,000 - 210,000; Full time

Job summary

Cerebras Systems seeks a deeply technical software engineer to join the on‑field Kernel Reliability team. You will improve reliability of our AI compute clusters and production services, coding close to the core to design scalable solutions.

New graduates are welcome to apply. You'll contribute to the technical roadmap for kernel‑centric reliability, reduce downtime with tooling and debugging support, enhance debug tools, and work across software, hardware and operations teams to steadily boost

Qualifications

• Strong programming skills in C/C++ and Python.
• Solid foundations in operating systems, computer architecture, and systems programming.
• Ability to debug complex issues using logs, traces, and standard debugging workflows; interest in root‑cause analysis.

Responsibilities

• Contribute to the technical roadmap and execution for kernel‑centric reliability of internal and customer‑facing systems.
• Partner with System and Cluster Operations teams to reduce downtime after failures through tooling and debugging support.
• Work with the Debug Team to enhance debug tools to speed up failure analysis.
• Collaborate with software teams to improve the software stack, including kernels, for better on‑field debugging.
• Co‑design next‑gen architectures with reliability and ease of debug in mind.
• Participate in incident response, root‑cause analysis, and post‑mortems; drive follow‑ups to improve reliability.

Skills

C/C++

Python

Operating systems

Systems programming

Debugging

Tools

Debuggers

Core dump handling

Tracing

Sanitizers

Profilers

Job description

Cerebras Systems seeks a deeply technical software engineer to join the on‑field Kernel Reliability team. You will improve reliability of our AI compute clusters and production services, coding close to the core to design scalable solutions.

New graduates are welcome to apply. You'll contribute to the technical roadmap for kernel‑centric reliability, reduce downtime with tooling and debugging support, enhance debug tools, and work across software, hardware and operations teams to steadily boost