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Listed location: Toronto Office
Work arrangement: remote. A remote label does not confirm worldwide eligibility or visa sponsorship.
Read the employer’s description for qualifications, compensation and work eligibility. Confirm the position is still open on the application page.
Job description supplied by Cerebras; category and skill labels may be inferred. How our listings work · Report a problem
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.
About The Role
The Inference Core Platform group is at the heart of Cerebras' mission to deliver the world’s fastest AI inference. Our team builds the foundational software and hardware infrastructure that powers low-latency, high-speed, high-throughput deployment on the Cerebras Wafer-Scale Engine (WSE). We are responsible for the full stack—from model compilation and scheduling down to custom hardware kernels and driver development.
The ML Performance Benchmarking team plays a pivotal role in shaping the performance and scalability of AI inference on one of the most advanced computing systems ever built. We drive the bring-up of core inference capabilities and deliver performance improvements at every stage of development – from early prototyping to production deployment.
We're looking for passionate engineers to join us in redefining the limits of AI inference. If you thrive on building systems that measure, analyze, and optimize performance at scale, this is your opportunity to make a transformative impact on the future of AI.
Scope of the team includes:
Core Inference Observability – Design and implement end-to-end telemetry systems across the software stack, providing deep visibility into inference performance and enabling rapid iteration before and after deployment.
Benchmarking Infrastructure – Architect, build, and scale the automation that generates, analyzes, and visualizes performance data used to inform business decisions across engineering and leadership.
Performance Analysis – Dive deep into system behavior, dissect performance bottlenecks, and deliver actionable insights that directly influence which features ship and how they evolve.
Feature Integration – Partner closely with Core Platform teams to define rigorous testing methodologies that validate inference features for peak performance.
Skills & Qualifications
Bachelor’s or Master’s degree in Computer Engineering, Systems Engineering, or a related field.
Proficiency in Python and/or C++ programming.
Proven experience in building and scaling automated infrastructure.
Strong background in throughput and performance optimization techniques, especially in complex, large-scale systems.
Excellent problem-solving skills and a strong analytical mindset.
Demonstrated ability to dive deep into new domains.
Ability to work in a fast-paced, ambiguous, and collaborative environment.
Preferred Skills & Qualifications
Familiarity with problem-solving at the intersection of hardware and software.
Hands-on experience with AI workloads and architectures is a plus.
Location
On-site or hybrid at our Toronto office
#LI-WA1
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined 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.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
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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Frequently asked questions
Is the ML Performance Benchmarking Engineer position at Cerebras remote?
Yes. The ML Performance Benchmarking Engineer role at Cerebras is a remote position. Country eligibility is not specified here; check the employer listing.
What type of employment is the ML Performance Benchmarking Engineer role?
Cerebras is hiring for a full-time ML Performance Benchmarking Engineer position.
Which skills are mentioned for the ML Performance Benchmarking Engineer job at Cerebras?
Detected skill labels include Python, C++, GPU. Check the employer description to distinguish required skills from preferred experience.
How do I apply for the ML Performance Benchmarking Engineer position at Cerebras?
You can apply for the ML Performance Benchmarking Engineer role directly through Cerebras's official application link provided on this page.
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