ML Systems Integration Engineer in Toronto

ML Systems Integration Engineer in Toronto

Toronto Full-Time 135000 - 165000 $ / year (est.) On-site
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At a Glance

  • Tasks: Join us in building next-gen AI hardware and software systems while debugging complex issues.
  • Company: Cerebras Systems, a leader in AI chip technology with a vibrant startup culture.
  • Benefits: Competitive salary, job stability, and a non-corporate work environment that values diversity.
  • Other info: Collaborative environment with opportunities for continuous learning and growth.
  • Why this job: Be part of a groundbreaking team transforming the AI landscape with ultra-fast supercomputers.
  • Qualifications: BS or MS in relevant fields, strong programming skills, and excellent problem-solving abilities.

The predicted salary is between 135000 - 165000 $ per year.

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.

Why Join Cerebras

  • Build a breakthrough AI platform beyond the constraints of the GPU.
  • Publish and open source their cutting-edge AI research.
  • Work on one of the fastest AI supercomputers in the world.
  • Enjoy job stability with startup vitality.
  • Our simple, non-corporate work culture that respects individual beliefs.

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.

ML Systems Integration Engineer in Toronto employer: Cerebras

Cerebras Systems is an exceptional employer for those passionate about advancing AI technology, offering a unique opportunity to work on the world's largest AI chip in a dynamic and innovative environment. With a strong emphasis on employee growth, a non-corporate culture that values individual beliefs, and the chance to contribute to groundbreaking projects alongside leading enterprises and startups, Cerebras fosters a collaborative atmosphere where engineers can thrive and make a meaningful impact. Join us to be part of a team that not only pushes the boundaries of AI but also prioritizes job stability and continuous learning.

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Contact Details:

Cerebras Recruitment Team

We think you need these skills to ace ML Systems Integration Engineer in Toronto

Python Programming
C++ Programming
Debugging Skills
Problem-Solving Skills
Operating Systems Fundamentals
Linux Development Environment
Computer Architecture Understanding