Cerebras Systems Inc. Logo

Cerebras Systems Inc.

ML Systems Performance Engineer

Posted One Month Ago
Remote
Hiring Remotely in Canada
Mid level
Remote
Hiring Remotely in Canada
Mid level
Drive end-to-end ML model inference performance: build kernel- and system-level performance models, optimize kernel microcode and compiler algorithms, debug runtime performance on system and cluster, and develop tooling to visualize and analyze performance data from the Wafer Scale Engine and compute cluster.
The summary above was generated by AI

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

Engineers on the inference performance team operate at the intersection of hardware and software, driving end-to-end model inference speed and throughput. Their work spans low-level kernel performance debugging and optimization, system-level performance analysis, performance modeling and estimation, and the development of tooling for performance projection and diagnostics.

Responsibilities
  • Build performance models (kernel-level, end-to-end) to estimate the performance of state of the art and customer ML models.

  • Optimize and debug our kernel micro code and compiler algorithms to elevate ML model inference speed, throughput and compute utilization on the Cerebras WSE.

  • Debug and understand runtime performance on the system and cluster.

  • Develop tools and infrastructure to help visualize performance data collected from the Wafer Scale Engine and our compute cluster.

Requirements
  • Bachelors / Masters / PhD in Electrical Engineering or Computer Science.

  • Strong background in computer architecture.

  • Exposure to and understanding of low-level deep learning / LLM math.

  • Strong analytical and problem-solving mindset.

  • 3+ years of experience in a relevant domain (Computer Architecture, CPU/GPU Performance, Kernel Optimization, HPC).

  • Experience working on CPU/GPU simulators.

  • Exposure to performance profiling and debug on any system pipeline.

  • Comfort with C++ and Python.

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:

  1. Build a breakthrough AI platform beyond the constraints of the GPU.

  2. Publish and open source their cutting-edge AI research.

  3. Work on one of the fastest AI supercomputers in the world.

  4. Enjoy job stability with startup vitality.

  5. 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.

This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.

Similar Jobs

32 Minutes Ago
Remote or Hybrid
Expert/Leader
Expert/Leader
Artificial Intelligence • Cloud • HR Tech • Information Technology • Productivity • Software • Automation
Lead a founding engineering team building a scalable, AI-powered product from the ground up. Own technical strategy, architecture, delivery, quality, reliability, and engineering standards. Hire, coach, and develop engineers and managers while shaping team culture. Partner with Product, Design, Security, Operations, Sales, and Customer Success to align roadmaps and release readiness. Drive AI-native capabilities, establish operating practices, and translate product strategy into executable engineering plans.
Top Skills: AIAi AgentsAutonomous WorkflowsCloud-Native InfrastructureData-Intensive ProductsDistributed SystemsFault ToleranceIntegration FrameworksObservabilityWorkflow Systems
42 Minutes Ago
Easy Apply
Remote or Hybrid
Canada
Easy Apply
Mid level
Mid level
Artificial Intelligence • Cloud • Computer Vision • Hardware • Internet of Things • Software
Manage enterprise customers after implementation, helping them achieve business value from Samsara’s IoT platform. Develop joint success plans, lead executive business reviews and customer workshops, recommend workflow improvements, explain platform capabilities, resolve barriers, and mentor Customer Success and Support teams. Collaborate with Sales, Support, Sales Engineering, Product, and Engineering while supporting customers across transportation, utilities, field services, and other physical-operation industries.
Top Skills: Internet Of Things (Iot)SaaS
3 Hours Ago
Easy Apply
Remote
Canada
Easy Apply
Entry level
Entry level
Cloud • Security • Software • Cybersecurity • Automation
Lead hands-on product security architecture across GitLab, including design reviews, threat modeling, systemic risk remediation, security standards, prototypes, and reusable developer guardrails. Partner with engineering and product leaders, secure distributed systems and software supply chains, guide AI coding tool security, mentor security engineers, and influence technical direction through proactive architecture and clear communication.
Top Skills: Ai Coding ToolsApplication SecurityDevsecopsDistributed SystemsSoftware Supply Chain SecurityThreat Modeling

What you need to know about the Calgary Tech Scene

Employees can spend up to one-third of their life at work, so choosing the right company is crucial, not just for the job itself but for the company culture as well. While startups often offer dynamic culture and growth opportunities, large corporations provide benefits like career development and networking, especially appealing to recent graduates. Fortunately, Calgary stands out as a hub for both, recognized as one of Startup Genome's Top 100 Emerging Ecosystems, while also playing host to a number of multinational enterprises. In Calgary, job seekers can find a wide range of opportunities.

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account