ML Systems Integration Engineer

Cerebras; Toronto; On-site; CAD 90,000 - 150,000; Full time

Job summary

Cerebras Systems is seeking a software engineer to participate in bringing up next‑generation AI hardware systems and supporting software. You will work across hardware and software domains to validate and stress distributed systems, while building automation that speeds debugging and validation tasks.

Ideal candidates have strong Python and C++, deep debugging skills, and a solid grounding in operating systems and computer architecture.

Qualifications

• BS or MS in Computer Science, Computer Engineering, Electrical Engineering, or related technical field.

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 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

Python

C++

Debugging

OS fundamentals

Linux development

Computer architecture

Analytical thinking

Cross‑team collaboration

Communication

Education

BS or MS in Computer Science/Computer Engineering or Electrical Engineering

Tools

Automation frameworks

Internal tooling

Diagnostic tools

Telemetry/log analysis

Job description

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

• 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

Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.

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