Senior CPU Performance Architect

Job Details: Job Description: Do Something Wonderful At Intel, we put silicon at the center of the world’s most meaningful innovations. From personal computing and AI to cloud-scale data centers and edge platforms, our processors power technologies that touch billions of lives. If you’re passionate about building world-class silicon at massive scale, we want to build the future with you. The Team You’ll join Intel’s All Cores Engineering (ACE) organization, the team responsible for designing and delivering Intel’s industry‑leading CPU cores. Within ACE, the Atom group focuses on high‑efficiency, performance‑per‑watt optimized cores that enable everything from client platforms to emerging edge and scalable solutions. This is a hands‑on senior engineering role with direct impact on next‑generation CPU silicon. What You’ll Do As a Senior CPU Design Verification Engineer you will play a critical role in ensuring architectural correctness, functional robustness, and power‑efficient performance of Intel’s Atom CPU designs before first silicon. Key responsibilities include but not limited to the following: Lead pre‑silicon functional verification of complex CPU and SoC logic to ensure full compliance with architectural and microarchitectural specifications. Develop and execute verification plans, testbenches, and SystemVerilog/UVM environments, ensuring comprehensive functional and coverage closure. Define, run, and analyze system‑level simulations to uncover functional, performance, power, and corner‑case issues. Debug and root‑cause complex RTL, microarchitecture, and integration issues; drive issues to resolution with design teams. Collaborate cross‑functionally with CPU architects, RTL de

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. Snowflake’s cloud spend is in billions of dollars per year. Hence, it is critical for us to govern and optimize our cloud spend, both for margins and long-term competitive advantage. Cloud Efficiency team’s charter is to build scalable products that enable governance, monitoring and optimization of cloud spend. Think of this as Observability for cloud costs and efficiency. The team’s vision is to “Transform cloud spend into a competitive advantage by empowering teams to continuously optimize the per-unit cost.” In order to improve the overall cloud efficiency (i.e. cost per unit), it is critical to build monitoring products that collate costs with other factors such as utilization, attribution, hardware performance and architecture. Hence, there is an opportunity to build a unified, self-serve cloud efficiency product across Snowflake, that delivers actionable, real-time efficiency datasets through streamlined user experiences. This will enable thousands of engineers at Snowflake and will elevate cloud efficiency at Snowflake for long-term success. When developing these solutions, we think about the problem end-to-end: how do we collect data from different stacks (e.g. costs from AWS, GCP, Azure and CPU, Memory, Utilization) across Snowflake reliably, how do we store it eff

Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. We're looking for an Engineering Program Manager — or a technical engineer ready to move into program management — to help drive execution on our RISC-V CPU team. You'll work across architecture, design, verification, physical design, and DFT to keep a high-performance CPU program moving from spec through tapeout and post-silicon debug. Partnering with a senior program lead and engineering managers, you'll own schedules, track milestones, surface risks early, and keep cross-functional teams aligned. This role is hybrid, based out of Austin, TX or Santa Clara, CA. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting. Who You Are Experience in CPU, SoC, or silicon development — as an engineer, technical lead, or program manager. Comfortable working with cross-functional engineering teams and translating technical detail into clear status, dependencies, and trade-offs. Organized and proactive; you chase down open items rather than waiting for them to resolve. A clear communicator who can hold your own in engineering discussions and write updates leadership can act on. What We Need Support the full CPU development cycle — spec, design, verification, DFT, ta

Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. We are looking for a highly technical Senior Staff/Principal Engineer to lead the porting and enablement of critical AI workloads. You will be a primary driver in migrating compute workloads to RISC-V architectures, ensuring our hardware is optimized for real-world application performance. The ideal candidate has a strong background in DevOps, workload porting, or application enablement . While this is an individual contributor role at its core, you will have the opportunity to grow and lead a small, specialized team over time as our workload migration efforts scale. This role is remote, based in the United States or Australia. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting. Who You Are A Technical Catalyst: You thrive on the challenge of driving AI hardware porting to RISC-V and making complex software stacks run efficiently on new hardware. Systems Expert: You possess deep knowledge of system software, compilers, or low-level OS internals. You are an expert in ARM or x86 environments and are ready to apply those skills to the RISC-V frontier. A Project Driver: You have the technical authority to lead the implementation of a compute migration to RISC-V through

NVIDIA is seeking a world-class computer architect to contribute to the development of future high-performance computing systems, with a focus on enhancing the power-constrained performance of the hardware. Ideal candidates will have a strong track record of understanding and analyzing memory systems architecture to improve performance per watt (perf/W) and performance per millimeter (perf/mm). A broad perspective across the field of computer architecture and depth in the area of power, performance, and area (PPA) analysis is highly desirable. NVIDIA has pioneered programmable GPUs and the CUDA language and is a world leader in high-performance computing technology, with aggressive plans for future processors. This position offers the opportunity to have a real impact in a fast-moving, technology-focused company. What you will be doing: Develop innovative high-performance processor and system architectures, focusing on the memory system and energy efficiency. Develop architecture and micro-architecture features to improve the state-of-the-art in GPU memory systems, optimizing along the axes of perf/W, perf/mm, and perf/$. Develop and enhance architecture prototype models for power and noise analysis. Participate in performance and power simulation of features to analyze, define, and improve energy per byte. Analyze benchmarks, application workloads, and performance/power simulation and emulation results to identify areas for architecture optimizations. Debug power, performance, and functional issues with high-level models, RTL simulation and emulation, silicon, and systems. Collaborate with outside partners on system infrastructure. What we want to see: 10+ yrs of experience in CPU/GPU architecture, memory systems design with a focus on energy efficiency in the system. Bachelor

NVIDIA is leading company of AI computing. At NVIDIA, our employees are passionate about AI, HPC , VISUAL, GAMING. Our SA team is more focusing to bring NVIDIA new technology into difference industries. We help to design the architecture of AI computing platform, analysis the AI and HPC applications to deliver our value to customers, focusing on defining and solving computational challenges in LLM inference and training acceleration, as well as network communication and data transfer optimization. What You'll Be Doing: Contribute to the development of open-source inference frameworks such as SGLang and vLLM, including feature and operator development, performance optimization, and model support, in collaboration with the community. Develop and optimize KV cache offloading frameworks for LLM workloads, supporting multi-level cache offloading and reuse across CPU, SSD, and remote storage to improve inference efficiency. (Team project: FlexKV) Drive R&D on compute performance in distributed training, and explore methods and technologies for performance optimization. Study computational challenges in machine learning systems, identify common needs and bottlenecks, and build example code, acceleration libraries, or frameworks accordingly. What We Need to See: Over 5 years working experience in the technology industry, with master’s degree or above in computer science, mathematics, electrical engineering, automation, or related fields. Strong interest in accelerated computing, parallel computing, and heterogeneous computing, with the motivation to explore these areas in depth. Solid programming skills, with a good understanding of data structures and computer systems fundamentals. Strong learning agil