ML Systems Integration Engineer

Responsibilities

• Participate in bring-up of next-generation AI hardware systems and supporting software infrastructure.
• Debug complex system-level issues spanning hardware and software interactions.
• Investigate failures occurring during system bring-up and identify root causes using logs, telemetry, and diagnostic tools.
• Build automation frameworks and internal tooling that improve system validation and debugging workflows.
• Develop software used to test, validate, and stress distributed hardware systems during development and production cycles.
• Collaborate closely with hardware engineers to isolate and resolve system integration issues.
• Improve system observability by building tools that surface failures quickly and accelerate debugging.
• Reproduce, triage, and diagnose difficult issues that arise during early hardware deployment.
• Support validation and qualification of new hardware generations as systems move toward production readiness.
• Continuously improve internal engineering workflows related to debugging, testing, and automation.

Skills & Qualifications

• BS or MS in Computer Science, Computer Engineering, Electrical Engineering, or related technical field.
• Strong programming skills in Python and/or C++.
• Excellent debugging and problem-solving skills with ability to investigate complex technical issues methodically.
• Solid understanding of operating systems fundamentals (processes, threads, memory management, concurrency, IPC).
• Experience working in Linux development environments.
• Understanding of computer architecture and interactions between hardware and software systems.
• Strong analytical thinking and ability to break down complex system failures into actionable root causes.
• Ability to work effectively across multiple engineering teams and collaborate in highly technical environments.
• Strong communication skills and willingness to work on ambiguous technical problems.

Preferred Skills & Qualifications

• Experience building automation frameworks, internal tooling, or test infrastructure
• Familiarity with distributed systems concepts
• Experience debugging large-scale systems or complex infrastructure environments
• Understanding of networking fundamentals and communication between distributed systems
• Experience working with hardware-adjacent software or system integration environments
• Familiarity with performance analysis, system telemetry, and log analysis
• Exposure to production systems validation or infrastructure reliability engineering

Why Join Cerebras

Apply today and become part of the forefront of groundbreaking advancements in AI!