דרושים » חשמל ואלקטרוניקה » ATE Engineer

As HW Architect Team Leader, you will combine deep technical leadership with people leadership. You will shape next-generation networking silicon while building and mentoring a strong architecture team.

What Youll Be Doing
Lead, manage, and mentor a team of HW architects, fostering technical excellence and innovation.
Drive research, evaluation, and architectural definition of next-generation SoCs - from product requirements through production.
Define next-generation Packet Processor / Datapath / Congestion Management architectures for high-performance, complex SoC Ethernet and NIC switches.
Lead system architecture and detailed micro-architecture definition across major functional blocks.
Collaborate cross-functionally with design, verification, modeling, software, and other architecture teams to ensure end-to-end system alignment.
Identify and evaluate new technologies, methodologies, and architectural approaches for future products.
Provide technical direction, make key architectural trade-offs, and ensure execution excellence.

*Part-Time or Full-Time Opportunity

In this job opening, we are seeking a highly motivated and visionary researcher to join our team focused on chiplet-based computing systems. This role involves research and development in chiplet-based architectures, aiming to overcome performance and scalability limits of traditional compute platforms.

Responsibilities:
Conduct cutting-edge research on the co-design of communication and computation for wafer-scale systems. On the communication side, the work focuses on architecting Networks-on-Chip, providing scalable, high-bandwidth, and ultra-low-latency interconnects that efficiently span multiple dies and support fine-grained data movement. On the computation side, the research emphasizes optimizing and mapping training and inference workloads to fully exploit wafer-scale resources, improving performance, scalability, and energy efficiency through intelligent task placement and scheduling.
Investigate various aspects of system design, including:
Network-on-Chip design, further including Topology exploration, routing algorithms, and protocol/flow-control design to support high-throughput collective communication, low-latency synchronization, and efficient model/data parallelism
Expressing and Mapping LLM Parallelism to Wafer-Scale System that simplify LLM parallelism (e.g., tensor, pipeline, and data parallelism) and efficiently map training and inference workloads onto wafer-scale system

*Part-Time or Full-Time Opportunity

Responsibilities:
The research focuses on designing next-generation rack and SuperPod architectures that combine elasticity through resource pooling with optimal performance enabled by holistic co-design across applications, parallel programming models, interconnect fabrics, and compute, memory, and switch chip architectures. On the communication side, the work architects scalable, high-bandwidth, and low-latency scale-up fabrics across multiple chips at rack and SuperPod scale. On the memory side, it explores richer protocol semantics beyond traditional load/store operations to reduce unnecessary data movement and rethinks memory hierarchies to expose large-scale capacity with near-local latency. On the compute side, it analyzes the requirements of General Compute and Generative AI workloads and their parallel programming models to fully leverage large-scale system resources.
Investigate and prototype new architectural features, including but not limited to:
o Tiered Memory: Explore advanced memory organizations, including hardware-managed caching, to enable software-transparent, fine-grained promotion and demotion of cache lines across the memory hierarchy.
o Prefetching/Speculation: Evaluate and design existing and next-generation hardware prefetching and speculation mechanisms to effectively hide local and remote memory latencies at rack and SuperPod scale.
o Near-Memory/Network Processing: Develop support for key primitives executed at the memory and network layers to minimize unnecessary data movement across sparse, dense, and pointer-based data structures.
o Workload-Centric Co-Design: Study optimal parallelization strategies at rack and SuperPod scale for both General Compute and Generative AI workloads, and design dedicated hardware support for widely used parallel programming primitives such as RPCs and collective communication.
Write reports and papers on the research results and present them.

The CPU Architect will take charge in defining a processor core that meets the requirement of high performance, high bandwidth, and scalable processing architecture. This architect will utilize his processor experience to deliver a world-class processor ASIC with many advanced features for Huawei products.

Our goal is to design cutting-edge CPUs for smartphones, servers, and desktops, and we need the very best talent to help us achieve it!
The CPU Micro architect will take charge in defining a processor Micro architecture features that will improve the performance and reduce the power consumption of the CPU core. This architect will use a performance simulator to explore his ideas and will analyze implementability of these features: Power, Timing, Area. This architect will utilize his processor and VLSI design experience to develop many advanced features for Huawei processors.