AI/ML ASIC Architect

Sandisk understands how people and businesses consume data and we relentlessly innovate to deliver solutions that enable today’s needs and tomorrow’s next big ideas. With a rich history of groundbreaking innovations in Flash and advanced memory technologies, our solutions have become the beating heart of the digital world we’re living in and that we have the power to shape. Sandisk meets people and businesses at the intersection of their aspirations and the moment, enabling them to keep moving and pushing possibility forward. We do this through the balance of our powerhouse manufacturing capabilities and our industry-leading portfolio of products that are recognized globally for innovation, performance and quality. Sandisk has two facilities recognized by the World Economic Forum as part of the Global Lighthouse Network for advanced 4IR innovations. These facilities were also recognized as Sustainability Lighthouses for breakthroughs in efficient operations. With our global reach, we ensure the global supply chain has access to the Flash memory it needs to keep our world moving forward. Description In this AI/ML ASIC Architecture position, you will develop AI Storage Solutions based advanced system architectures and AI/ML Accelerator ASIC architecture specifications for Sandisk’s next generation products. You will drive, initiate, and analyze frontend architecture of the AI/ML Accelerator product. As an AI/ML ASIC Architect you will help drive new architecture initiatives that leverage the state-of-the-art frontend interfaces like UCIe, PCIe, CXL, etc that integrates AI Storage Solutions with xPU in a 3D package system. You will drive the AI Storage Solutions based architecture. You will exercise your technical expertise and excellent communication skills to collaborate with design and product planning with an eye towards delivering innovative and highly competitive adaptive accelerators solutions. Typical activities include writing architecture spec, working with other architects in the team, work with RTL/DV/Simulation/Emulation/FW teams to evaluate these changes and assess the performance, power, area, and endurance of the product. You will work closely with excellent colleague engineers, cope with complex challenges, innovate, and develop products that will change the data centric architecture paradigm. Essential Duties And Responsibilities Responsible for driving the AI/ML ASIC architecture that integrates the AI Storage with GPU/TPU/xPU accelerators, with a particular focus on I/O subsystems connected over UCIe/ PCIe/CXL Author architecture specifications in clear and concise language for AI/ML xPU based Accelerator using AI Storage Solutions. Define I/O subsystem and PCIe DMA architectures, including their interactions with internal embedded processor-subsystems, Network on Chip, Memory controllers, and FPGA fabric. Create flexible and modular I/O subsystem architectures that can be deployed in either Chiplet, monolithic or 3D form factors. Work with customers, and cross-functional teams to scope SoC requirements, analyze PPA tradeoffs, and then define architectural requirements that meet the PPA and schedule targets. Define SoC subsystem and DMA hardware, software, and firmware interactions with embedded processing subsystems and SoC CPUs on the device side and Host CPUs. Author architecture specifications in clear and concise language. Guide and assist pre-silicon design/verification and post-silicon validation during the execution phase. Responsible for improving the AI/ML ASIC Architecture performance through hardware & software co-optimization, post-silicon performance analysis, and influencing the strategic product roadmap. Work with customers, and cross-functional teams to scope SoC requirements, analyze PPA tradeoffs, and then define architectural requirements that meet the PPA and schedule targets. Guide and assist pre-silicon design/verification and post-silicon validation during the execution phase. LLM Workload analysis and characterization of ASIC and competitive datacenter and AI solutions to identify opportunities for performance improvement in our products. Experience architecting one or some components of AI/ML accelerator ASICs such as HBM, PCIe/UCIe/CXL, NoC, DMA, Firmware Interactions, NAND, xPU, fabrics, etc Drive the AI Storage Solutions frontend system architecture with GPU/TPU/NPU/xPU to match or exceed the nextgen HBM bandwidth Architect memory-efficient inference/training systems utilizing techniques like pruning, quantization with MX format , continuous batching/chunked prefill, and speculative decoding Collaborate with internal and external stakeholders/ML researchers to disseminate results and iterate at rapid pace Required Bachelors or Masters or PhD in Computer/Electrical Engineering with 15+ years of hands-on Architecture experience authoring specifications Strong technical background architecting ASIC, SoC, or I/O subsystems involving PCIe/UCIe/CXL and DMA engines Knowledge of I/O Subsystem and DMA interactions with internal embedded processor-subsystems (x86, RISC-V or ARM) and external host CPU Good understanding of computer/graphics architecture, ML, LLM Architecting an GPU/TPU/xPU Accelerator systems with optimized high bandwidth memory hierarchy and frontend architecture for multi-trillion parameter LLM training/inference including Dense, Mixture of Experts (MoE) with multiple modalities (text, vision, speech) KV cache optimization, Flash Attention, Mixture of Experts Deep experience optimizing large-scale ML systems, GPU architectures Proficiency in principles and methods of microarchitecture, software, and hardware relevant to performance engineering Knowledge of ARM Processors and AXI Interconnects Preferred Familiarity and background in UCIe, CXL, NVLink, or UAL microarchitecture and protocols is a plus Familiarity with High-speed networking: InfiniBand, RDMA, NVLink is a plus Expert knowledge of transformer architectures, attention mechanisms, and model parallelism techniques Multi-disciplinary experience, including familiarity with Firmware and ASIC design Expertise in CUDA programming, GPU memory hierarchies, and hardware-specific optimizations Proven track record architecting distributed training systems handling large scale systems Previous experience with NVMe storage systems, protocols, and NAND flash - advantage Additional Information Sandisk is committed to providing equal opportunities to all applicants and employees and will not discriminate based on their race, color, ancestry, religion (including religious dress and grooming standards), sex (including pregnancy, childbirth or related medical conditions, breastfeeding or related medical conditions), gender (including a person’s gender identity, gender expression, and gender-related appearance and behavior, whether or not stereotypically associated with the person’s assigned sex at birth), age, national origin, sexual orientation, medical condition, marital status (including domestic partnership status), physical disability, mental disability, medical condition, genetic information, protected medical and family care leave, Civil Air Patrol status, military and veteran status, or other legally protected characteristics. We also prohibit harassment of any individual on any of the characteristics listed above. Our non-discrimination policy applies to all aspects of employment. We comply with the laws and regulations set forth in the Equal Employment Opportunity is the Law poster. Sandisk thrives on the power and potential of diversity. As a global company, we believe the most effective way to embrace the diversity of our customers and communities is to mirror it from within. We believe the fusion of various perspectives results in the best outcomes for our employees, our company, our customers, and the world around us. We are committed to an inclusive environment where every individual can thrive through a sense of belonging, respect and contribution. Sandisk is committed to offering opportunities to applicants with disabilities and ensuring all candidates can successfully navigate our careers website and our hiring process. Please contact us at View email address on click.appcast.io to advise us of your accommodation request. In your email, please include a description of the specific accommodation you are requesting as well as the job title and requisition number of the position for which you are applying. #J-18808-Ljbffr Sandisk