ML Software Tool Development Engineer

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. Responsibilities: Lead the design and implementation of system-level debugging, validation, and observability platforms. Develop automated systems for collecting and analyzing numerical, and execution anomalies. Create visualization and analysis tools to enable efficient root-cause investigation. Build frameworks for failure classification, regression detection, and anomaly monitoring. Extend compilers, runtimes, and programming interfaces to support advanced profiling and instrumentation. Improve system bring-up, low-level debug, and validation workflows. Partner cross-functionally with compiler, hardware, firmware, runtime, and infrastructure teams. Establish best practices for debuggability, reliability, and operational excellence. Lead high-impact initiatives. Support incident response and drive long-term corrective actions. Skills & Qualifications Strong proficiency in C++ and Python, with a track record of building reliable, high-performance systems and tooling. Demonstrated experience debugging complex hardware/software systems and driving issues to root cause. Experience analyzing system-level data structures, execution graphs, or dependency networks for diagnostics and validation. Proven ability to design and build intuitive visualization and analysis tools for comple