Soc Compute Memory Subsystem Architect Jobs

Job Details: Job Description: About the Role The CEG NAG (Networking Architecture Group) is Intel's premier team focused on defining the future of high-performance networking silicon. Our team architects next-generation networking solutions that enable hyperscale data centers, cloud infrastructure, and AI workloads to achieve unprecedented performance and efficiency. We specialize in IPU/DPU platforms, advanced packet processing architectures, and programmable networking technologies that form the backbone of modern distributed computing systems. We are seeking a Senior SoC Compute & Memory Architect to define and drive the architecture of compute complexes and high-performance memory subsystems for next-generation IPU/DPU platforms. This role is responsible for end-to-end architecture of CPU clusters, cache hierarchies, coherency models, and memory subsystems. You will optimize system-level performance, scalability, power efficiency, and programmability while ensuring seamless interaction with networking, storage, and accelerator subsystems in hyperscale environments. What You’ll Do Key responsibilities will include but not limited to: Cache Hierarchy and Coherency Architecture 1. Define and evolve multi-level cache hierarchy (private/shared caches, system-level cache). 2. Architect coherency models across compute cores, accelerators, and IO subsystems (coherent vs non-coherent interactions). 3. Evaluate tradeoffs between latency, bandwidth, scalability, and coherence domain complexity. Memory Subsystem Architecture 1. Architect system memory subsystems including: -DDR / LPDDR interfaces. -Memory controllers and scheduling policies. -Bandwidth provisioning and scaling strategies. 2. Work with Perfo

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. Tenstorrent is seeking a SoC Design Verification Engineer to lead pre-silicon verification of the Beowulf SoC, with focus on the Compute Subsystem (CSS), DDR memory subsystem, and Fabric NoC. This role will drive coverage, coherency, memory traffic, connectivity, error handling, and bring-up features critical to silicon success. This role is hybrid, based out of Boston, MA; Toronto, ON; 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 Deeply curious about SoC architecture, compute systems, DDR behavior, and Fabric NoC/interconnect verification. Expert in UVM, SystemVerilog, coverage-driven verification, assertions, and subsystem-level debug. Experienced in verifying compute subsystems, DDR controllers and PHY-facing logic, NoC/interconnect protocols, coherency, ordering, and data movement. Comfortable with reset, power management, error handling, performance, and high-concurrency system scenarios. Proactive, detail-oriented, and effective in cross-functional technical discussions. Familiar with Python, C/C++, Tcl, CocoTB, or similar verification automation tools. What We Need Develop and own scalable verification environmen

About the job Shape the SoC architecture behind Graphcore's next generation of AI acceleration platforms. Graphcore is expanding its Silicon Architecture Team in Bristol to deliver complex AI compute platforms. As a SoC Architect, you will define how critical subsystems are specified, modelled and integrated. You will turn product requirements into architecture choices across interfaces, interconnect, memory and platform behaviour. Your work will guide implementation, validation and trade-offs across multiple chip programmes. You will work with processor, SoC and system architects, plus design, verification, hardware and software teams. Together, you will evaluate IP, resolve integration questions and support silicon bring-up where needed. This is a rare chance to influence real AI silicon while Graphcore scales its contribution to SoftBank Group's AI ecosystem. The team and culture The team owns SoC architecture, subsystem modelling and system-level trade-offs across future AI acceleration platforms. Work moves from requirements to specifications, models, reviews and guidance for implementation teams. People here are expected to take responsibility early and keep decisions moving. You will speak directly with adjacent teams to clarify constraints, challenge assumptions and close open questions. Decisions are made through technical evidence, clear specifications and direct cross-functional discussion. The team values people who think big, act fast and speak up when architecture needs sharper choices. What we're looking for • Experience specifying or architecting complex SoC devices or subsystems. • Strong understanding of computer architecture, SoC integration, RTL development and verification processes. • Ability to turn product requirements into clear technical specifications and practical design trade-offs. • Software development capability, ideally with Python, C++, Rust or architecture modelling experience. • Knowledge of PCIe, LPDDR, DDR, E

NVIDIA is now looking for a Senior Memory System Engineer to join our ASIC Memory Subsystem team! As a Senior Systems Engineer at NVIDIA, you'll join a group of hardworking engineers to develop and architect innovative Memory Solution for Tegra SoCs. In this position, you'll make a real impact in a multifaceted, technology-focused company. You will work with memory controller/PHY and Platform / System architect, Firmware, SI/PI, Memory suppliers to design and architect cutting edge, high speed and lower power memory technology for NVIDIA CPUs and SOCs. What You Will Be Doing: Analyze future DDR/LPDDR/HBM technologies to determine optimum performance, power, function and RAS in memory for Next generation SOC and Systems. Collaborate with ASIC Architects, Designers, Software and Firmware SW/FW teams to drive memory technology and associated requirements for memory controllers. Define Memory module, Package, and PCB layouts appropriate to the system workloads Debug and bring up memory evaluation / validation and failure issues on memory technology. Collaborate with DRAM suppliers and industry partners on to develop memory and memory related component technology. What We need to see: Bachelor's degree or master’s degree in Electrical Engineering, Computer Engineering (CE), or a related field (or equivalent experience) 10 years of proven track record in DRAM design, module design, or memory sub system design. Deep understanding and strong fundamental of memory design, features, ECC algorithm, SI and PI (Training algorithm) in DDR, LPDDR, and HBM. Strong understanding of memory sub system level interaction with Cache, Memory controller and PHY. Experience in the design, bring-up and validation for memory failure analysis Experience with Python, C/C

About the Team OpenAI’s Hardware organization develops AI-native silicon and system-level solutions for the unique demands of advanced AI workloads. Building on efforts like Jalapeño, the team is developing future generations of AI-native silicon and tightly integrated systems to power the next generation of frontier models. By co-designing chips, systems, tools, and methodologies, the team helps deliver faster, more efficient, and production-ready hardware for OpenAI’s supercomputing platform. About the Role We are seeking an experienced SoC Architect to lead the definition and development of next-generation custom AI silicon for edge deployments. This role will be responsible for shaping the architecture of highly efficient, high-performance SoCs optimized for machine learning inference and on-device intelligence. You will work cross-functionally with internal engineering teams and external ecosystem partners to translate product requirements into scalable silicon solutions, driving execution from concept through delivery. In this role you will: Define the architecture and technical roadmap for custom SoCs targeted for edge applications. Drive system-level tradeoff analysis across compute, memory, interconnect, power, thermal, and cost constraints. Architect energy-efficient ML compute subsystems optimized for inference workloads and real-world deployment environments. Collaborate with internal hardware, software, systems, and product teams to align architecture with platform needs. Partner with external silicon vendors, IP providers, and manufacturing partners to execute development plans. Lead hardware/software co-design efforts to maximize performance per watt and end-to-end system efficiency. Guide implementation teams through microarchitecture, RTL development, validation, and bring-up phases. Operate effectively in agile development environments and help teams deliver against aggressive schedules and milestones. You might thrive in this role if: Proven exper

About the Team OpenAI’s Hardware organization develops AI-native silicon and system-level solutions for the unique demands of advanced AI workloads. Building on efforts like Jalapeño, the team is developing future generations of AI-native silicon and tightly integrated systems to power the next generation of frontier models. By co-designing chips, systems, tools, and methodologies, the team helps deliver faster, more efficient, and production-ready hardware for OpenAI’s supercomputing platform. About the Role We are looking for a highly experienced RTL engineer to own critical on- and off-chip interconnect components for our custom AI accelerator platform. You will drive the microarchitecture and RTL implementation of scalable on-chip communication fabrics connecting high-bandwidth compute, memory, and I/O subsystems as well as purpose-built off-chip interfaces and protocols needed to enable custom computing at scale. This is a senior, hands-on engineering role with broad technical ownership. You will drive design from requirements through the full silicon lifecycle, from architecture definition and performance analysis through RTL implementation, verification closure, physical design convergence, bring-up, and production readiness. You will plan and oversee the work of junior engineers and help drive and develop productive engineering relationships with external partners and help manage partner execution. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Own the microarchitecture, RTL design, and delivery of major SoC interconnect components, including network-on-chip fabrics, switches, routers, bridges, protocol adapters, arbiters, and traffic-management logic as well as off-chip protocol bridges and interfaces. Drive third party engagements to develop novel networking and interface protocols and silicon IP while ensuring high quality and de

About the Team: OpenAI’s Hardware organization develops AI-native silicon and system-level solutions for the unique demands of advanced AI workloads. Building on efforts like Jalapeño, the team is developing future generations of AI-native silicon and tightly integrated systems to power the next generation of frontier models. By co-designing chips, systems, tools, and methodologies, the team helps deliver faster, more efficient, and production-ready hardware for OpenAI’s supercomputing platform. About the Role OpenAI is developing custom silicon to power the next generation of frontier AI models. We’re looking for experienced Design Verification (DV) Engineers to ensure functional correctness and robust design for our cutting-edge ML accelerators. You will play a key role in verifying complex hardware systems—ranging from individual IP blocks to subsystems and full SoC—working closely with architecture, RTL, software, and systems teams to deliver reliable silicon at scale. In this role you will: Own the verification of one or more of: custom IP blocks, subsystems (compute, interconnect, memory, etc.), or full-chip SoC-level functionality. Define verification plans based on architecture and microarchitecture specs. Develop constrained-random, directed, and system-level testbenches using SystemVerilog/UVM or equivalent methodologies. Build and maintain stimulus generators, checkers, monitors, and scoreboards to ensure high coverage and correctness. Drive bug triage, root cause analysis, and work closely with design teams on resolution. Contribute to regression infrastructure, coverage analysis, and closure for both block- and top-level environments. You might thrive in this role if you have: BS/MS in EE/CE/CS or equivalent with 3+ years of experience in hardware verification. Proven success verifying complex IP or SoC designs in industry-standard flows Proficient in SystemVerilog, UVM, and common simulation and debug tools (e.g., VCS, Questa, Verdi). Strong knowledge

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. As a SoC Design Engineer, you will be part of the Heterogeneous Integration Group (HIG), contributing to the design, development, and integration of next‑generation HBM SoC logic die. You will work closely with architecture, verification, physical design, firmware, and product teams to implement robust, high‑performance SoC solutions that meet ambitious power, performance, area, and schedule targets. You will also work to enable and integrate AI-driven tools and AI-enabled workflows into the team's methodologies. Key Responsibilities Design and implement RTL for SoC‑level blocks and subsystems used in HBM logic die. Integrate internal and third‑party IP (e.g., controllers, microcontrollers, NOC, RAS, MBIST, interfaces, adapters, buffers, PHY‑adjacent logic). Collaborate with SoC architects to translate architectural and micro‑architectural specifications into high‑quality RTL implementations. Participate in SoC‑level integration activities, including clocking, reset, power intent, and configuration infrastructure. Assist with pre‑silicon validation and post‑silicon bring‑up, including root‑cause analysis of silicon issues. Contribute to design documentation, block specifications, and design reviews. Collaborate multi-functionally with Product Engineering, Test, Probe, Process Integration, and Manufacturing to ensure robust and manufacturable builds. Minimum Qualifications Bachelor’s or master’s degree in electrical engineering, Computer Engin

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. As a SoC Design Engineer, you will be part of the Heterogeneous Integration Group (HIG), contributing to the design, development, and integration of next‑generation HBM SoC logic die. You will work closely with architecture, verification, physical design, firmware, and product teams to implement robust, high‑performance SoC solutions that meet ambitious power, performance, area, and schedule targets. This is a hands-on technical role passionate about RTL build, IP integration, debugging, and pre/post-silicon support. Key Responsibilities Design and implement RTL for SoC‑level blocks and subsystems used in HBM logic die. Integrate internal and third‑party IP (e.g., controllers, microcontrollers, NOC, RAS, MBIST, interfaces, adapters, buffers, PHY‑adjacent logic). Collaborate with SoC architects to translate architectural and micro‑architectural specifications into high‑quality RTL implementations. Participate in SoC‑level integration activities, including clocking, reset, power intent, and configuration infrastructure. Assist with pre‑silicon validation and post‑silicon bring‑up, including root‑cause analysis of silicon issues. Contribute to design documentation, block specifications, and design reviews. Collaborate multi-functionally with Product Engineering, Test, Probe, Process Integration, and Manufacturing to ensure robust and manufacturable builds. Minimum Qualifications Bachelor’s or master’s degree in electrical engineering, Computer

NVIDIA's invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, we are increasingly known as “the AI computing company”. We are looking to grow our company, and grow our teams with the smartest people in the world. What you’ll be doing: You will work with ground breaking technologies for the Tegra SoC and various NVIDIA embedded platforms Implement power and thermal management software features in Linux Kernel and user space Collaborate with power architects, hardware and software engineers on platform power estimation and optimization Optimize the software stack to improve performance, efficiency, and responsiveness for edge AI and robotics use cases. Focus on improving compute and memory utilization, reducing latency and power consumption, and tuning system-level performance to deliver reliable and scalable AI workloads across demanding real-world edge environments. What we need to see: MS in CS, CE, EE, Systems Engineering or related software/hardware engineering major, or equivalent experience 8+ years of software development experience with a significant focus on Linux Excellent C programming/debugging skills within Linux kernel and user space software Background with working on embedded systems and ARM processor specific System-level debugging experience and problem-solving skills Excellent communication skills Ways to stand out from the crowd: Understanding of the Linux power and thermal management features (schedule

EnCharge AI is a leader in advanced AI hardware and software systems for edge-to-cloud computing. EnCharge’s robust and scalable next-generation in-memory computing technology provides orders-of-magnitude higher compute efficiency and density compared to today’s best-in-class solutions. The high-performance architecture is coupled with seamless software integration and will enable the immense potential of AI to be accessible in power, energy, and space constrained applications. EnCharge AI launched in 2022 and is led by veteran technologists with backgrounds in semiconductor design and AI systems. The Role We are seeking a thorough SOC Physical Verification & Integration Specialist to drive the physical assembly and signoff of our next-generation SOCs. In this role, you will own the physical integration strategy from the floorplan stage through to tapeout, ensuring seamless assembly of massive multi-hierarchical blocks. You will act as the critical bridge between block-level implementation, top-level integration, and final foundry signoff, ensuring that complex physical bottlenecks are resolved without compromising power, performance, or area (PPA). Key Responsibilities Top-Level Physical Integration: Drive the full-chip physical assembly of very large-scale SOCs (e.g., multi-billion transistor designs). Manage top-level floorplanning, bump planning, global power grid (PG) integration, and top-level clock/routing integration. Hierarchical Verification Methodology: Architect and deploy highly efficient, hierarchical physical verification (PV) flows. Define the boundary conditions, abstraction models, and interface rules required to assemble heavily partitioned, massive-scale designs. Signoff Execution & Debugging: Own full-chip DRC, LVS, ERC, Antenna, ESD, and Latch-up signoff using industry-standard tools (e.g., Siemens Calibre) at advanced process nodes (5nm, 3nm, or below). Cross-Functional Collaboration: Partner tightly with the Physical Design (PD

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. The Architecture team at Tenstorrent is designing the central compute chiplet that powers our next generation automotive SoC. This role is about turning real world automotive and safety requirements into architecture that performs, scales, and ships fast and reliably. If you think silicon design should start with clarity and end with confidence, this is where your experience makes the biggest impact. This role is remote, based in Munich, Germany. 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 Approach design with a systems mindset, always thinking in trade offs, not just specs and block diagrams. Bring deep knowledge of SoC architecture, from interconnects and I/O to memory and CPUs. Confident working within performance, power, and reliability constraints. Familiar with, or eager to dive into, functional safety, ISO 26262, and automotive grade design challenges. What We Need Someone to architect and specify one or more chiplets in the robotics and automotive family. 5+ years of experience translating high level requirements into detailed architectural direction. Ability to identify impactful features that boost PPA, safety, and reliab

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 Staff Digital Design Engineer to help define, build, and optimize high-performance IP and SoC architectures for next-gen AI and compute workloads. This role is ideal for engineers who thrive at the intersection of microarchitecture, RTL implementation, and performance-aware design. This role is hybrid, based out of Toronto, Ottawa, Boston, or Austin. 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 digital design expert with a deep understanding of computer architecture and IP microarchitecture. Skilled in RTL development (Verilog/VHDL) and familiar with full ASIC flows. Comfortable optimizing for power, performance, and area (PPA) under aggressive design goals. A naturally collaborative and technical engineer — you thrive in spec definition, peer reviews, and team-wide planning. What We Need Architecture and RTL implementation of Tenstorrent’s custom IP blocks and SoC components. Performance-aware design decisions for compute, interconnect, or memory-heavy blocks. Occasional contributions to validation using emulation, FPGA prototyping, or UVM flows. Strong synthesis and timing closure awareness to support backend

EnCharge AI is a leader in advanced AI hardware and software systems for edge-to-cloud computing. EnCharge’s robust and scalable next-generation in-memory computing technology provides orders-of-magnitude higher compute efficiency and density compared to today’s best-in-class solutions. The high-performance architecture is coupled with seamless software integration and will enable the immense potential of AI to be accessible in power, energy, and space constrained applications. EnCharge AI launched in 2022 and is led by veteran technologists with backgrounds in semiconductor design and AI systems. Staff Engineer: STA Methodology & Sign-off Lead We are seeking a high-caliber Staff or Senior Staff Engineer to architect and lead our SOC Static Timing Analysis (STA) Methodology along with execution responsibilities to eliminate the bottle-necks in STA and build bridges. This is a critical role for a forward-thinking engineer who excels at defining the frameworks and flows required to navigate the complexities of modern, large-scale SOC designs. Engineer will have scope to bridge Architecture, CAD, RTL, and Physical Design to establish a predictable, high-performance, and scalable path to tape-out. The Role As the lead for STA Methodology, you will own the sign-off architecture and the timing convergence strategy. Rather than just executing runs, you will build the "engine" that enables execution—defining flows, qualifying tools, establishing margin strategies (AOCV/LVF/POCV), and driving cross-functional alignment to meet aggressive Power, Performance, and Area (PPA) targets. Key Responsibilities Sign-off Methodology & Architecture: Define and own full-chip SOC timing sign-off criteria, including Multi-Mode Multi-Corner (MMMC) definitions, derate strategies, and operating condition mapping for functional, shift, and capture modes. Flow Development & Left-Shift Automation: Architect, deploy, and maintain adva

EnCharge AI is a leader in advanced AI hardware and software systems for edge-to-cloud computing. EnCharge’s robust and scalable next-generation in-memory computing technology provides orders-of-magnitude higher compute efficiency and density compared to today’s best-in-class solutions. The high-performance architecture is coupled with seamless software integration and will enable the immense potential of AI to be accessible in power, energy, and space constrained applications. EnCharge AI launched in 2022 and is led by veteran technologists with backgrounds in semiconductor design and AI systems. About the Role EnCharge AI is looking for an Embedded SW Engineer to develop the firmware for our Edge AI processors. The candidate must possess an excellent understanding of computer architecture and operating system concepts including, but not limited to, memory management, virtualization and PCIe address space. The role includes designing and developing the core Firmware for various parts of the SOC. The candidate must possess strong communication skills to interface with Runtime, Architecture and H/W teams. Responsibilities Develop the critical pieces of EAI Firmware used to deploy inference jobs on EAI processors Validate different IP blocks on the SOC Evaluate and integrate third-party device drivers to interface with EnCharge’s SW stack Work closely with the Runtime, Hardware and Architecture teams define the driver architecture Qualifications Bachelors in EE/CS Advanced programming skills in C/C++ for operating system kernel & systems development Understanding of RISC-V architecture is a plus Exposure to PCIe BAR and IOMMU architecture Exposure to virtualization and hypervisor technologies Deep understanding of operating systems concepts, data structures, x86-64 and accelerator architectures Experience with low-level debug tools as well as emulators and simulators Experience running, analyzing, and tuning system performance benchmarks Excellent verb