Intel jobs

CPU Performance Architect, Silicon New Taipei, Banqiao District, New Taipei City, Taiwan; +1 more As a CPU Performance Architect, you will be the key contributor to improve processor instruction set architecture, to develop innovative microarchitecture features, and deliver Google's advanced SoC products. You will collaborate cross-functionally with android applications and AI teams to conduct applications and benchmark performance analysis and to project their performance at various design phases. You will be guided by architects and work with engineers in Power, Thermal, Security, and Physical Design teams to determine the CPU subsystem configuration and features. Google's mission is to organize the world's information and make it universally accessible and useful. Our team combines the best of Google AI, Software, and Hardware to create radically helpful experiences. We research, design, and develop new technologies and hardware to make computing faster, seamless, and more powerful. We aim to make people's lives better through technology. Develop and modify a performance model for performance analysis and microarchitecture study. Evaluate Advanced RISC Machine (ARM's) architecture features from both architecture and performance angles. Define and write CPU subsystem architecture specifications. Collaborate with Register-Transfer Level (RTL), design verification, and physical design teams to develop a high-performance and efficient CPU implementation. Manage performance correlation between the performance model and RTL implementation, including micro-benchmark development and pre-silicon and post-silicon performance bug triage. Minimum qualifications: Bachelor's degree in Electrical Engineering, Computer Engineering or Computer Science, with a focus on computer architecture, or equivalent practical experience. 4 years of experience in microprocessor

CPU Architecture and Performance Architect New Taipei, Banqiao District, New Taipei City, Taiwan Be part of a team that pushes boundaries, developing custom silicon solutions that power the future of Google's direct-to-consumer products. You'll contribute to the innovation behind products loved by millions worldwide. Your expertise will shape the next generation of hardware experiences, delivering unparalleled performance, efficiency, and integration. As a CPU architecture and performance architect, you'll be the key contributor to improve processor instruction set architecture, to develop innovative microarchitecture features, and to deliver Google's advanced SoC products. You'll have the opportunity to collaborate with talents in system performance and software teams to plan and conduct application and benchmark performance analysis and to project their performance at various design phases. Leveraging your CPU-specific knowledge and leadership, you'll be guiding junior CPU architects and working with engineers in power, thermal, security, and physical design teams to determine the CPU subsystem configuration and features. Google's mission is to organize the world's information and make it universally accessible and useful. Our team combines the best of Google AI, Software, and Hardware to create radically helpful experiences. We research, design, and develop new technologies and hardware to make computing faster, seamless, and more powerful. We aim to make people's lives better through technology. Drive performance correlation between the performance model and RTL implementation, including micro-benchmark development, pre-silicon performance correlation, and post-silicon performance analysis and debugging. Plan and evaluate CPU architecture features from both architecture and performance angles. Develop a performance model for

Performance 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 Join Cerebras as a Performance Engineer within our innovative Runtime Team. Our groundbreaking CS-3 system, hosted by a distributed set of modern and powerful x86 machines, has set new benchmarks in high-performance ML training and inference solutions. It leverages a dinner-plate sized chip with 44GB of on-chip memory to surpass traditional hardware capabilities. This role will challenge and expand your expertise in optimizing AI applications and managing computational workloads primarily on the x86 architecture that run our Runtime driver. Responsibilities - Focus on CPU

Performance & Reliability Engineer Sunnyvale, CA; 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 Join Cerebras as a Performance & Reliability Engineer within our innovative Co-Design and Next Generation Team. Our groundbreaking CS-3 system has set new benchmarks in high-performance ML training and inference solutions. It leverages a dinner-plate sized chip with 44GB of on-chip memory to surpass traditional hardware capabilities. This role focuses on characterizing and optimizing the performance and reliability of state-of-the-art AI models running on Cerebras' breakthrough hardware. Responsibilities - Characterize and enhance the performance and reliability of advanced ML hardware/software

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 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

Senior CPU Power Management Architect 2 Locations posted: Posted 30+ Days Ago

Senior CPU Design Verification Engineer 2 Locations posted: Posted 25 Days Ago

Intel Foundry Process TD Frame CellSet Engineer US, Oregon, Hillsboro posted: Posted 30+ Days Ago

Intel 729jobs Location not specified

Senior Runtime 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 We are building the next generation of large-scale AI systems that power training and inference workloads at unprecedented scale and efficiency. You will design and develop high-performance distributed software that orchestrates massive compute and data pipelines across heterogeneous clusters. Your work will push the limits of concurrency, throughput, and scalability-enabling efficient execution of models at massive scale. This role sits at the intersection of systems engineering and machine learning performance, demanding both architectural depth and low-level implementation skills. You will help

Full Stack Engineer – Manufacturing Test 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. About the Role As a Full Stack Engineer focusing on Cerebras' manufacturing test platform, you will design, build, and maintain a comprehensive test software solution for all stages of manufacturing - from individual components to complete Cerebras systems. You will collaborate cross-functionally with hardware design, engineering, operations, and data analytics teams to develop user interfaces and data processing frameworks that directly impact manufacturing efficiency, quality, and scalability. Responsibilities - Collaborate with hardware engineers and test developers to create frameworks that facilitate the development, validation,

Intel 150jobs Location not specified

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

Mechanical\Materials\Chemical Engineering Student for Intel Kiryat Gat Israel, Kiryat-Gat posted: Posted 30+ Days Ago

Manufacturing Student Technician – Intel Contract Employee Ocotillo Technology Fabrication (OTF) US, Arizona, Phoenix posted: Posted 3 Days Ago

Senior Analog IP Integration, Power, and SI Engineer 2 Locations posted: Posted 4 Days Ago

Business Intel Reports Developer Location not specified

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

Graduate Talent (System and Hardware Enabling Engineer) Malaysia, Penang posted: Posted 8 Days Ago

Security & IT General Opportunities 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 Team Our IT & Security team sits at the intersection of security, infrastructure, and cutting-edge AI systems. The team plays a critical role in ensuring Cerebras' environments are secure, reliable, scalable, and ready to support customers operating at the frontier of AI. We are looking for people who care deeply about operational excellence, security best practices, automation, and building systems that can support a rapidly growing organization. What You May Work On Depending on the role and team needs, you

Threat Intel Analyst Lithuania - Vilnius posted: Posted 30+ Days Ago

Business Intel Specialist II Manila posted: Posted 17 Days Ago

CPU Performance Architect US, Texas, Austin posted: Posted 30+ Days Ago