Strong Compute jobs

Machine Learning Compute Efficiency Lead, Infrastructure & Planning Cupertino, United States of America Apple's Platform Acceleration & Compute Efficiency (PACE) is a high-leverage team operating at the critical intersection of our ML organizations, underlying compute infrastructure, and core platform tooling. Our mission is to empower Apple's software engineering teams with efficient, scalable compute. By driving out operational friction and optimizing the broader machine learning ecosystem, we directly accelerate the pace of development across the company. As foundation models become increasingly central to Apple's user experiences, maximizing the efficiency of our ML compute is paramount. In this role, you will focus relentlessly on compute efficiency, ensuring that Apple's models run as fast, reliably, and cost-effectively as possible. You will tackle massive optimization challenges, from maximizing hardware utilization across GPUs, TPUs, and custom Apple Silicon, to shaping workload scheduling and capacity allocation for large model serving. We are seeking a Senior Architect with deep expertise in ML infrastructure to act as a linchpin for Apple's foundational inference strategy. You will be instrumental in defining, establishing, and monitoring compute efficiency metrics across the software engineering organization. By partnering closely with model developers and infrastructure providers, your work will directly reduce serving costs, shape core engineering decisions, and enable the highly efficient, scalable inference required to power Apple Intelligence for hundreds of millions of users. - Own and support ML compute management for Apple's inference workloads (GPU, TPU, and custom silicon) to enable large-scale model serving. - Collaborate closely with Apple Intelligence and ML

Compute Specialist - SLED (State Local and Education) All, Illinois, United States of America Embrace the opportunity to become a Compute Specialist and drive sales of advanced SLED solutions for federal clients. Leverage your expertise in solution selling, account management, and IT to build strong client relationships and exceed quotas. Shape the future of enterprise IT with Hewlett Packard Enterprise in a dynamic, remote-friendly environment.

Compute Sales Specialist - VA / DC All, Virginia, United States of America Embrace the role of a Compute Sales Specialist and drive growth by leading sales of advanced technology solutions. Leverage your expertise in solution selling, project management, and account planning to build strong client relationships and exceed quotas. Enjoy a flexible, remote work environment with opportunities for professional development and impactful contributions.

Compute Sales Specialist - Stamford, CT Stamford, Connecticut, United States of America Embrace the role of a Compute Sales Specialist and drive growth by leading sales initiatives, managing complex accounts, and leveraging your expertise in software solutions. Collaborate with cross-functional teams, build strong client relationships, and shape the future of IT sales in a dynamic, remote-friendly environment. Grow your career with a global industry leader.

Compute Sales Specialist Taguig City, National Capital Region (Manila), Philippines Embrace the role of a Compute Sales Specialist and drive growth by leveraging your expertise in specialty sales and solution selling. Collaborate with IT professionals, manage client relationships, and help shape innovative IT solutions. If you excel at prospecting, negotiation, and building strong client partnerships, this is your opportunity to make an impact.

Compute Server Platform Architect Sunnyvale CA or Toronto Canada Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. Our novel wafer-scale architecture provides the AI compute power of dozens of GPUs on a single chip, with the programming simplicity of a single device. This approach allows Cerebras to deliver industry-leading training and inference speeds and empowers machine learning users to effortlessly run large-scale ML applications, without the hassle of managing hundreds of GPUs or TPUs. Cerebras' current customers include top 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. Thanks to the groundbreaking wafer-scale architecture, Cerebras Inference offers the fastest Generative AI inference solution in the world, 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. About The Role As a Compute / Server Platform Architect on the Cluster Architecture Team, you will own the server-side platform architecture that enables Cerebras CS3-based AI clusters (training and inference) to deliver predictable performance, scalability, and reliability. Our accelerators are network-attached, so the x86 server fleet is a first-class part of the end-to-end system: it runs critical-path runtime functions (for example orchestration, prompt caching, and IO/control services) and must be co-designed with software for token-level latency, throughput, and cost efficiency. You will

Principal Member of Technical Staff BENGALURU, KARNATAKA, India, IN OCI Compute is looking for strong Senior Software Developers with a strong cloud/distributed systems/microservices background to take on the challenge of engineering Compute Infrastructure solutions and build services for Large Scale Compute and performance while providing strong guarantees of availability to our customers. Your team will have diverse expertise in systems, compute, networking and software development to provide the stability, performance, and reliability that our customers need. OCI has taken the lead in becoming the premiere Cloud Provider of next gen computing, and this is your opportunity to play a role in the Compute industry movement. Design and develop compute software in Java and other languages. Apply engineering principles for defining robust and maintainable architectures and designs. Build cloud service on top of the modern Infrastructure as Service (IaaS) building blocks at OCI Design, lead and build distributed, scalable, fault tolerant software systems Participate in the entire software lifecycle - development, testing, CI/CD and production operations Collaborate broadly across multiple disciplines from designers to developers. Identify requirements, scope solutions, estimate work, schedule deliverables. Help establish and drive the adoption of outstanding coding standards and patterns and help enhance our inclusive engineering culture. Balance between product feature development, troubleshooting and production operational concerns like ops automation, structured logging, instrumentation for metrics and participating in on-call. Career Level - IC4

Senior Security Engineer New Haven, CT At Quantum Circuits Inc., we are building the world's first truly algorithmic quantum computers to achieve transformational computing capabilities. Our full-stack quantum computing platform uses superconducting devices along with a modular, robust, and scalable architecture. Our unique approach is based on a decade of technology research and breakthroughs at Yale University's world-renowned quantum labs. We are seeking a highly skilled and self-motivated Senior Security Engineer to join our dynamic team. The ideal candidate has a strong background in evaluating and mitigating security vulnerabilities across on-premises and AWS environments and will be hands-on in assessing, designing, implementing, and maintaining a robust security posture for all systems. This ensures QCI's infrastructure is secure, resilient, and capable of supporting our cutting-edge quantum computing platform. At Quantum Circuits Inc., we are building the world's first truly algorithmic quantum computers to achieve transformational computing capabilities. Our full-stack quantum computing platform uses superconducting devices along with a modular, robust, and scalable architecture. Our unique approach is based on a decade of technology research and breakthroughs at Yale University's world-renowned quantum labs. We are seeking a highly skilled and self-motivated Senior Security Engineer to join our dynamic team. The ideal candidate has a strong background in evaluating and mitigating security vulnerabilities across on-premises and AWS environments and will be hands-on in assessing, designing, implementing, and maintaining a robust security posture for all systems. This ensures QCI's infrastructure is secure, resilient, and capable of supporting our cutting-edge quantum computing platform. Key Responsibilities:

Lead Full Stack Machine Learning Engineer Bengaluru, Karnataka, India Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. Our novel wafer-scale architecture provides the AI compute power of dozens of GPUs on a single chip, with the programming simplicity of a single device. This approach allows Cerebras to deliver industry-leading training and inference speeds and empowers machine learning users to effortlessly run large-scale ML applications, without the hassle of managing hundreds of GPUs or TPUs. Cerebras' current customers include top 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. Thanks to the groundbreaking wafer-scale architecture, Cerebras Inference offers the fastest Generative AI inference solution in the world, 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. About T he Role This teams' principal responsibility is to rapidly bring up state-of-the-art open-source models, frameworks and data engineering. Success in this role requires a system-minded generalist who thrives in fast-paced bringup environments and is comfortable working across the entire software stack. Your work will play a critical role in achieving unprecedented levels of performance, efficiency, and scalability for AI applications. Responsibilities - Contribute to the end-to-end bring up of frameworks for RL, inference serving, ML models on Cerebras CSX systems. -

Advanced Technology: Compiler Engineer Sunnyvale, CA; Vancouver, British Columbia, Canada Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. Our novel wafer-scale architecture provides the AI compute power of dozens of GPUs on a single chip, with the programming simplicity of a single device. This approach allows Cerebras to deliver industry-leading training and inference speeds and empowers machine learning users to effortlessly run large-scale ML applications, without the hassle of managing hundreds of GPUs or TPUs. Cerebras' current customers include top 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. Thanks to the groundbreaking wafer-scale architecture, Cerebras Inference offers the fastest Generative AI inference solution in the world, 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. About The Team Cerebras builds wafer-scale AI processors-single chips delivering tens of PB/s of memory bandwidth and a dataflow architecture that accelerates at a granularity no multi-device system can match. The Advanced Technology Group (ATG) is Cerebras ' pathfinding organization. We work ahead of product to explore new architectures, demonstrate breakthrough performance on scientific and AI workloads, and shape the technical roadmap for future Cerebras hardware and software. Our work regularly appears at top-tier venues (Supercomputing, SIAM, IEEE, and NeurIPS ) and

Quantum Solutions Scientist Tsukuba, Japan Summary QuEra Computing is seeking a qualified candidate to help develop algorithms and applications in collaboration with external customers, collaborators, and users. With an outcome-oriented mindset, you will work on projects ranging from machine learning, operations research, data science, chemistry, and more. Working individually and as part of a team, you will interact with clients, business partners, collaborators, and other users of quantum computers to implement algorithms, develop use-cases, and create business solutions that leverage near and intermediate-term neutral atom quantum computers. QuEra Computing is the leader in neutral atom quantum computing, and is a front runner in the race towards utility-scale quantum computing. In this role, you will be at the cutting edge of quantum computing development. Your contributions and ideas will help steer QuEra and the entire field to practical quantum utility. Qualifications - MSc or a Ph.D. degree in applied mathematics, computer science, physics, or a related discipline, or equivalent professional experience - Expert knowledge of at least one of the fields of quantum machine learning, quantum optimization, quantum chemistry, or quantum information science - Strong knowledge of the fundamentals of quantum computing and algorithmic primitives - Strong written and verbal communication skills - Ability to collaborate effectively across multidisciplinary teams - Proficiency in Python - Strong written and verbal communications skills in both English and Japanese Preferred Qualifications - Expertise in an industry vertical such as logistics, finance, operations research, chemistry, biotech, engineering, machine learning, or other related field - Experience

Quantum Scientist - Machine Learning and Quantum Error Correction Boston, MA, USA Summary QuEra Computing is seeking a talented, impact-motivated researcher with strong expertise in quantum error correction and decoding. You will be part of the team to develop and implement quantum error correction protocols and decoding algorithms on our unique hardware, with a particular focus on the use of machine learning methods for decoding and QEC design. You will have the opportunity to work with a vibrant community of academic and industry collaborators, and to help our growing team of diverse experts address fascinating challenges, from the development of hardware-efficient error correction schemes and decoding algorithms for our unique Rydberg atom quantum computer, to the design of protocols for executing fault-tolerant quantum logic, and finally to the implementation of fault-tolerant quantum algorithms with these methods. Required Qualifications - PhD in Physics, Computer Science, Mathematics, Electrical Engineering, or equivalent experience - Experience in machine learning for scientific problems - Experience in quantum computing and quantum error correction - An exceptional publication record in relevant fields - Strong written and verbal communication skills - Strong software skills Preferred Qualifications - Experience simulating error correction protocols - Experience collaborating with experimental teams and/or implementing error correction protocols on hardware - Experience with high-performance software development and real-time operations The approximate base salary range for this position is $130,400 - $211,900. We consistently monitor external market data and update base salary ranges accordingly. We determine base compensation decisions on several factors, including as

Senior Quantum Scientist - Quantum + AI Boston, MA, USA Summary QuEra is seeking a talented AI scientist to explore the intersection of quantum computing and AI. This includes topics in "quantum for AI", such as development of quantum machine learning algorithms for generative tasks, integration of quantum computers into AI workflows, and augmentation of classical training with quantum methods. This may also include topics in "AI for quantum", such as AI compilation techniques for hardware execution, machine characterization and inference, decoding, and related topics. A strong candidate is expected to have deep hands-on experience with contemporary classical AI workflows, such as the large language models (LLMs), a strong understanding of the underlying theory of modern AI, and an understanding of quantum computing and quantum information theory. As part of your role, you will spearhead efforts at QuEra to develop the next generation of quantum and AI algorithms guided by your experience with classical AI approaches. The role will include both cutting-edge research, as well as development and deployment of algorithms on the next generation of neutral-atom hardware. QuEra Computing is the leader in neutral-atom quantum computing, and is a front runner in the race towards utility-scale quantum computing. In this role, you will be at the forefront of integrating quantum algorithms with practical AI-driven toolchains, driving innovation across simulation, optimization, and quantum machine learning domains. Qualifications - PhD in math, computer science, quantum physics, or equivalent professional experience - Strong hands-on expertise with modern AI/ML methods, such as deep

Quantum Scientist - Quantum Error Correction and Decoding Boston, MA, USA Summary QuEra Computing is seeking talented, impact-motivated researchers with strong expertise in quantum error correction and decoding. You will be part of the team to develop and implement quantum error correction protocols and decoding algorithms on our unique hardware. You will have the opportunity to work with a vibrant community of academic and industry collaborators, and to help our growing team of diverse experts address fascinating challenges, from the development of hardware-efficient error correction schemes and decoding algorithms for our unique Rydberg atom quantum computer, to the design of protocols for executing fault-tolerant quantum logic, and finally to the implementation of fault-tolerant quantum algorithms with these methods. Qualifications - PhD in Quantum Computing, Physics, Computer Science, Mathematics, Electrical Engineering, or equivalent experience - Strong background in quantum computing and quantum error correction - An exceptional publication record in relevant fields - Strong written and verbal communication skills - Strong software skills Preferred Qualifications - Experience implementing high-performance decoders, including both software and hardware implementations - Experience simulating error correction protocols - Experience collaborating with experimental teams and/or implementing error correction protocols on hardware - Experience with high-performance software development and real-time operations - Experience with machine learning methods The approximate base salary range for this position is $130,400 - $211,900. We consistently monitor external market data and update base salary ranges accordingly. We determine base compensation decisions on several factors, including as geographic placement, role-specific knowledge, skills, and/or experience.

Software Development Manager, EC2 Core Consoles Arlington, Virginia, USA The Amazon EC2 team is seeking a very strong technical leader to manage and grow an engineering team that focuses on building the web applications that enable customers to launch and manage Amazon Elastic Cloud Compute (EC2) instances and other AWS resources. This requires a thorough knowledge of what it takes to develop scalable, extensible technology, as well as how to structure and develop engineering organizations. Amazon Web Services (AWS) provides Amazon's customers with access to in-the-cloud infrastructure services based on Amazon's own back-end technology platform, which developers can use to enable virtually any type of business. Amazon EC2 is the web service that is pioneering cloud computing by providing resizable compute capacity in the cloud. It gives any developer complete control of their computing resources and lets them run on Amazon's proven computing environment. We are continuing to build the team in order to expand on our feature set and manage our rapidly increasing scale. We are expanding our capacity management initiatives to support high growth at large scales and create novel markets to support the computing needs of our customers. The ideal candidate is passionate about the large opportunity that Amazon EC2 presents and is eager for a significant intellectual, technical and operational challenge. This person has thrived and succeeded in delivering high quality solutions in a fast-growth environment where priorities shift fast. The position demands excellent technical skills and knowledge coupled with strong leadership, planning, and management abilities.

Engineering Manager, Kernel Reliability Sunnyvale CA or Toronto Canada Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. Our novel wafer-scale architecture provides the AI compute power of dozens of GPUs on a single chip, with the programming simplicity of a single device. This approach allows Cerebras to deliver industry-leading training and inference speeds and empowers machine learning users to effortlessly run large-scale ML applications, without the hassle of managing hundreds of GPUs or TPUs. Cerebras' current customers include top 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. Thanks to the groundbreaking wafer-scale architecture, Cerebras Inference offers the fastest Generative AI inference solution in the world, 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. The Role We're looking for a deeply technical, hands-on engineering leader for our on-field Kernel Reliability team. You will lead a high performing team to tackle a critical challenge: improving the reliability of our advanced compute clusters and the underlying inference, training, and internal production services. In this role, you'll set the technical vision while staying close to the code and designing solutions that will scale to our exponentially growing system production and software service offerings. If you have proven expertise in software

Principal Engineer, AI Inference Reliability Remote, California, United States; Sunnyvale CA or Toronto Canada Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. Our novel wafer-scale architecture provides the AI compute power of dozens of GPUs on a single chip, with the programming simplicity of a single device. This approach allows Cerebras to deliver industry-leading training and inference speeds and empowers machine learning users to effortlessly run large-scale ML applications, without the hassle of managing hundreds of GPUs or TPUs. Cerebras' current customers include top 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. Thanks to the groundbreaking wafer-scale architecture, Cerebras Inference offers the fastest Generative AI inference solution in the world, 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. In late 2024, we launched Cerebras Inference, the fastest Generative AI inference service in the world, over 10 times faster than GPU-based hyperscale cloud inference. Since launch, we've scaled to meet the surging demand from AI labs, enterprises, and a thriving developer community. In October 2025, we announced our series G funding, raising $1.1 billion USD to accelerate the expansion of our products and services to meet global AI demand. About the team The Cerebras Inference team's mission

Internship - Photonics Design Boston, MA, USA About QuEra Computing, Inc. QuEra Computing is building the world's most powerful neutral-atom quantum computers. Our systems are designed to scale and enable groundbreaking advances in science and technology. We collaborate closely with leading academic and industry partners to push the boundaries of quantum computing, error correction, and fault tolerance. Summary The Photonics team at QuEra pioneers cutting-edge photonic chips for integration into neutral-atom quantum computers. QuEra Computing Inc. seeks a Photonic Engineer Intern to help build the AI-driven design pipelines that will accelerate next-generation PIC development. You will explore state-of-the-art optimization workflows, directly improving how quickly our engineers can iterate and tape out novel photonic components for large-scale neutral-atom quantum computers. Responsibilities - AI-Powered Photonics Design: Explore and build AI-driven photonics design and optimization pipelines to accelerate the component design. - Design for Manufacturing: Incorporate Design of Experiments (DoE) and Design for Manufacturing (DfM) principles into PIC design to improve yield and process robustness across multiple foundries. - Cross-functional Collaboration: Partner with photonics engineers and systems teams to align PIC designs with the requirements of neutral-atom quantum computer integration. Qualifications - Pursuing or recently completed a degree in computer science, physics, mathematics, or a related field. - Strong programming skills in using Python and AI tools. - Proficient with PIC development tools and advanced optimization algorithms for PIC design. - Strong understanding of PIC fundamental physics and foundry processes. - Experience incorporating Design of Experiments (DoE) and Design for Manufacturing (DfM) into

Software Engineer, Kernel Reliability Sunnyvale CA or Toronto Canada Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. Our novel wafer-scale architecture provides the AI compute power of dozens of GPUs on a single chip, with the programming simplicity of a single device. This approach allows Cerebras to deliver industry-leading training and inference speeds and empowers machine learning users to effortlessly run large-scale ML applications, without the hassle of managing hundreds of GPUs or TPUs. Cerebras' current customers include top 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. Thanks to the groundbreaking wafer-scale architecture, Cerebras Inference offers the fastest Generative AI inference solution in the world, 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. About The Role We're looking for a deeply technical, hands-on software engineer to join our on-field Kernel Reliability team. You'll help tackle a critical challenge: improving the reliability of our advanced compute clusters and the underlying inference, training, and internal production services. In this role, you'll work close to the code and design solutions that will scale with our rapidly growing system production and software service offerings. If you have strong fundamentals in systems, debugging, and failure analysis-and enjoy building tools and solving

Staff Python / PyTorch Developer — Frontend Inference Compiler – Dubai Europe; Remote, California, United States; UAE Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. Our novel wafer-scale architecture provides the AI compute power of dozens of GPUs on a single chip, with the programming simplicity of a single device. This approach allows Cerebras to deliver industry-leading training and inference speeds and empowers machine learning users to effortlessly run large-scale ML applications, without the hassle of managing hundreds of GPUs or TPUs. Cerebras' current customers include top 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. Thanks to the groundbreaking wafer-scale architecture, Cerebras Inference offers the fastest Generative AI inference solution in the world, 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. About the Role: Would you like to participate in creating the fastest Generative Models inference in the world? Join the Cerebras Inference Team to participate in development of unique Software and Hardware combination that sports best inference characteristics in the market while running largest models available. Cerebras wafer scale inference platform allows running Generative models with unprecedented speed thanks to unique hardware architecture that provides fastest access to local memory, ultra-fast interconnect and huge amount

Postdoctoral Fellow - Computational Biology & Medicine - Jhunjhunwala Lab South San Francisco, California, United States of America This position offers a unique opportunity to be jointly mentored by experts in our Computational Biology and Medicine department and our Oncology Research organization. Strong experience in applicatio...

ASIC Architect Sunnyvale, CA Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. Our novel wafer-scale architecture provides the AI compute power of dozens of GPUs on a single chip, with the programming simplicity of a single device. This approach allows Cerebras to deliver industry-leading training and inference speeds and empowers machine learning users to effortlessly run large-scale ML applications, without the hassle of managing hundreds of GPUs or TPUs. Cerebras' current customers include top 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. Thanks to the groundbreaking wafer-scale architecture, Cerebras Inference offers the fastest Generative AI inference solution in the world, 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. Responsibilities - Translate high level architecture spec to micro-architecture feature requirements - Bring up new features in the performance/power model - Perform comprehensive PPA trade-offs for new architectural features - Extract insights for new features and micro-architecture power efficiency - Profile workloads, identify bottlenecks and project competition performance for benchmarking - Engage with SW teams for end-end application level modeling at cluster level - Identify kernel level HW acceleration level opportunities Qualifications - Masters/PhD in Electrical/Computer Engineering - 10+ years of experience across performance analysis and modeling across

ML Systems Performance Engineer Sunnyvale CA or Toronto Canada Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. Our novel wafer-scale architecture provides the AI compute power of dozens of GPUs on a single chip, with the programming simplicity of a single device. This approach allows Cerebras to deliver industry-leading training and inference speeds and empowers machine learning users to effortlessly run large-scale ML applications, without the hassle of managing hundreds of GPUs or TPUs. Cerebras' current customers include top 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. Thanks to the groundbreaking wafer-scale architecture, Cerebras Inference offers the fastest Generative AI inference solution in the world, 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. 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 Performance Benchmarking Engineer Toronto, Ontario, Canada Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. Our novel wafer-scale architecture provides the AI compute power of dozens of GPUs on a single chip, with the programming simplicity of a single device. This approach allows Cerebras to deliver industry-leading training and inference speeds and empowers machine learning users to effortlessly run large-scale ML applications, without the hassle of managing hundreds of GPUs or TPUs. Cerebras' current customers include top 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. Thanks to the groundbreaking wafer-scale architecture, Cerebras Inference offers the fastest Generative AI inference solution in the world, 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. 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