Performance Engineer at Cerebras Systems | Toronto, Ontario

Cerebras Systems is revolutionizing AI with the largest AI chip globally, measuring 56 times larger than traditional GPUs. Our innovative wafer-scale architecture delivers the computational power of numerous GPUs on a single chip, combining unparalleled performance with the simplicity of a single device. This unique approach enables Cerebras to provide leading-edge training and inference speeds, allowing machine learning professionals to effortlessly execute large-scale ML applications without the complexities of managing multiple GPUs or TPUs.Cerebras counts among its esteemed clients top-tier model laboratories, major global enterprises, and pioneering AI-native startups. Recently, OpenAI announced a multi-year collaboration with Cerebras, aiming to deploy 750 megawatts of power to transform critical workloads with ultra-high-speed inference.The groundbreaking wafer-scale architecture of Cerebras Inference offers the fastest Generative AI inference solution worldwide, exceeding GPU-based hyperscale cloud inference services by over ten times. This dramatic improvement in speed is reshaping the user experience of AI applications, facilitating real-time iterations and enhancing intelligence through advanced agentic computation.About The RoleJoin Cerebras as a Performance Engineer within our innovative Runtime Team. Our cutting-edge CS-3 system, powered by a network of modern and robust x86 machines, has established new benchmarks in high-performance ML training and inference solutions. Leveraging a chip the size of a dinner plate with 44GB of on-chip memory, this role will challenge and expand your expertise in optimizing AI applications and managing computational workloads primarily on the x86 architecture that supports our Runtime driver.

Cerebras Systems is at the forefront of AI technology, having developed the world's largest AI chip, which is 56 times larger than traditional GPUs. Our revolutionary wafer-scale architecture delivers unparalleled AI compute power equivalent to dozens of GPUs on a single chip, combined with the ease of programming as if it were a single device. This innovative approach enables us to achieve industry-leading training and inference speeds, allowing machine learning practitioners to run extensive ML applications effortlessly, without the complexities associated with managing numerous GPUs or TPUs. Cerebras is trusted by leading model labs, global enterprises, and pioneering AI-native startups. Notably, OpenAI recently announced a multi-year partnership with Cerebras, aimed at deploying 750 megawatts of scale, revolutionizing critical workloads with ultra high-speed inference. Thanks to our groundbreaking wafer-scale architecture, Cerebras Inference offers the fastest Generative AI inference solution globally, exceeding GPU-based hyperscale cloud inference services by more than 10 times. This significant enhancement in speed is redefining the user experience of AI applications, facilitating real-time iterations and amplifying intelligence through enhanced agentic computation.About The RoleAs a member of the inference performance team, you will work at the critical intersection of hardware and software, enhancing end-to-end model inference speed and throughput. Your focus will encompass low-level kernel performance debugging and optimization, system-level performance analysis, performance modeling, and the creation of tools for performance diagnostics and projections.ResponsibilitiesDevelop performance models (kernel-level, end-to-end) to forecast the performance of state-of-the-art and client ML models.Optimize and troubleshoot our kernel micro code and compiler algorithms to enhance ML model inference speed, throughput, and compute utilization on the Cerebras WSE.Analyze and debug runtime performance at the system and cluster level.Create tools and infrastructure to visualize performance data collected from the Wafer Scale Engine and our compute cluster.

Cerebras Systems is at the forefront of AI innovation, creating the world’s largest AI chip, a staggering 56 times larger than traditional GPUs. Our revolutionary wafer-scale architecture delivers the computational power of dozens of GPUs within a single chip, paired with the simplicity of a unified programming interface. This unique approach enables us to achieve unparalleled training and inference speeds, empowering machine learning practitioners to execute large-scale ML applications effortlessly, without the complexities associated with hundreds of GPUs or TPUs.Among our esteemed clientele are leading model laboratories, global enterprises, and pioneering AI-native startups. Recently, OpenAI announced a multi-year collaboration with Cerebras, aiming to leverage 750 megawatts of scale to revolutionize key workloads through ultra-high-speed inference.Thanks to our groundbreaking wafer-scale architecture, Cerebras Inference provides the fastest Generative AI inference solution available today, boasting speeds over ten times faster than GPU-based hyperscale cloud services. This extraordinary increase in speed is reshaping the user experience of AI applications, enabling real-time iterations and enhancing intelligence through advanced agentic computation.About The RoleJoin our inference model team, dedicated to advancing state-of-the-art models by numerically validating and accelerating innovative concepts on our wafer-scale hardware. In this role, you will prototype architectural enhancements, construct performance evaluation pipelines, and translate quantitative insights into actionable changes that drive production success.Key ResponsibilitiesPrototype and benchmark innovative concepts such as new attention mechanisms, mixture of experts (MoE), speculative decoding, and other emerging advancements.Create agent-driven automation tools that design experiments, schedule runs, triage regressions, and prepare pull requests.Collaborate closely with compiler, runtime, and silicon teams, gaining a unique perspective on the complete software/hardware innovation stack.Stay current with the latest open- and closed-source models; execute them on wafer scale first to identify new optimization opportunities.

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Join our dynamic team at ApprovalMax as a Revenue Systems Engineer, where you'll play a pivotal role in enhancing our go-to-market (GTM) systems stack. This position is crucial for the build, management, and continuous improvement of our GTM systems.As a member of the Revenue Operations team, you will focus on technical execution and maintaining the operational reliability of GTM systems. You will work under the guidance of established architectural frameworks set forth by our central Product and Data leadership, who oversee system-of-record decisions and uphold company-wide data standards.This hands-on role requires you to implement approved solutions, safeguard system integrity, and ensure operational excellence across our GTM tools on a daily basis. You will report directly to the RevOps Team Lead and enjoy a hybrid work environment, spending 2-3 days a week in our Toronto office.Core ResponsibilitiesGTM Integrations & Data Flow (Execution)Implement and maintain integrations between HubSpot, the data warehouse, the product platform, and supporting GTM tools.Create API-based data syncs using Python or Node.js, adhering to defined integration standards.Ensure integrations are reliable, observable, and thoroughly documented.Monitor integrations and promptly resolve operational issues according to agreed escalation processes.Identify and flag architectural or systemic risks to the appropriate stakeholders.HubSpot Systems AdministrationAdminister HubSpot on a daily basis, focusing on:Custom objects, properties, and associationsWorkflows and automationConfigure HubSpot in line with RevOps governance and global data models.Support integrations with adjacent GTM tools (e.g., dialers, enrichment, marketing, and customer success platforms).Data Quality & Governance SupportImplement data quality standards, validation rules, and hygiene processes.Assist with deduplication and lifecycle management processes.Ensure that upstream data quality supports downstream reporting and analytics.Escalate data governance inquiries or structural changes to designated global owners.Collaboration & EnablementCollaborate with RevOps, Sales, Marketing, Customer Success, and Product teams to translate approved requirements into technical solutions.Document systems, integrations, and operational processes clearly.Support the rollout of GTM tools and process improvements from both implementation and support perspectives.

Join the Ontario Transit Group as a PLC Technician, where you will play a vital role in maintaining and improving our automated systems. In this full-time position, you will work alongside a dedicated team of professionals, ensuring the reliability and efficiency of our transit operations.As a PLC Technician, your responsibilities will include troubleshooting PLC systems, performing regular maintenance, and collaborating with engineering teams to enhance system performance. Your expertise will directly contribute to our mission of providing safe and efficient transit services.

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