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# ML Software Tool Development Engineer

- **Company:** Cerebras Systems
- **Location:** United States
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), C++ (Programming Language), Communications Protocols, Data Structures, Software Debugging, Distributed Computing Environment, Firmware, Hardware Interface Design, Python (Programming Language), Machine Learning, Software Tools, Software Systems, Technical Data Management Systems, Build Management
- **Published:** July 24, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=ed3a377231ad5bb4

## About the Role

* 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 complex technical data.
 * Experience with compiler internals, custom hardware interfaces, or low-level protocol design.
 * Strong written and verbal communication skills, with the ability to explain technical concepts to diverse stakeholders.
 * Ability to work independently and lead complex technical projects end-to-end.

Preferred Skills & Qualifications

 * Familiarity with machine learning training and inference pipelines, especially distributed training and large-model scaling.
 * Prior work on high-performance clusters, HPC systems, or custom hardware/software co-design.

## Description

* 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.


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