דרושים » הנדסה » HW Architect team leader

We are a highly experienced architecture group specializing in switch processing, with deep expertise in both hardware and software architecture in the high-speed networking domain.
Our innovative packet processors power some of the most advanced data centers in the world and are designed into tier-1 vendor platforms. With state-of-the-art technology, a strong track record of industry recognition, and multiple award-winning achievements, we continuously push the boundaries of performance and scalability.
Our group is involved across the entire development lifecycle - from early research and architectural definition to silicon production - working on both research initiatives and production-grade products.


What will you be doing?
Lead research, evaluation, and architectural definition of next-generation chips - from requirements through production.
Define next-generation Packet Processor / Datapath / Congestion Management architectures for high-performance, complex SoC Ethernet Switches.
Design the system architecture and detailed micro-architecture definition across major functional blocks.
Collaborate closely with design, verification, and modeling teams to ensure architectural intent is fully realized.
Work cross-functionally with other architecture teams to shape cohesive system solutions.
Explore and evaluate new technologies and innovative approaches for future products.

We are looking for a Principal Engineer with deep expertise in database internals, system architecture, and hardware-aware performance optimization.
This role is responsible for defining and driving advanced database performance solutions by understanding and improving the interaction between database engines, operating systems, and modern hardware architectures.
The ideal candidate is an experienced technical leader with a strong background in database systems, performance engineering, and computer architecture. The candidate should be capable of leading complex technical initiatives, influencing architectural decisions, and developing innovative solutions for next-generation database platforms.
This is a hands-on technical leadership role requiring expertise across database kernels, query execution, transaction processing, memory systems, and low-level performance optimization.

Responsibilities
Define and drive technical direction for database performance optimization and hardware-aware database architecture.
Lead the design and implementation of advanced database optimizations focused on scalability, efficiency, and workload performance.
Solve complex performance challenges across the full system stack, including database engines, query execution, transaction processing, concurrency control, storage engines, operating systems, and hardware platforms.
Design and develop optimizations leveraging modern hardware architectures, including multi-core CPUs, large-memory systems, NUMA platforms, CXL memory, RDMA networking, and advanced storage technologies.
Improve database execution engines, caching mechanisms, memory management, storage systems, and workload scheduling.
Analyze system behavior and identify bottlenecks using profiling, tracing, hardware performance counters, and low-level performance analysis.
Develop benchmarks, workload models, and methodologies to evaluate scalability, efficiency, and architectural tradeoffs.
Collaborate with database kernel, infrastructure, and engineering teams to influence architecture decisions and deliver high-impact improvements.
Mentor senior engineers and contribute to building technical expertise across the organization.
Drive innovation through research, prototyping, technical analysis, and architectural improvements.

We are looking for a Senior AI Modeling Architect to define and model the architecture of our next-generation AI processors. In this role, you will serve as a key technical authority - bringing not only strong modeling capabilities, but also the architectural vision to propose and drive end-to-end solutions to complex design challenges.
You will work at high levels of abstraction, partnering closely with HW and SW architects to co-invent optimal solutions, validate them through simulation, and influence design decisions based on experimental data.

Responsibilities
Model CPU/AI processor functionality and performance using SystemC and pre-silicon simulation environments.
Define and drive architectural solutions - not only identify problems, but come with concrete proposals and alternatives.
Partner with lead HW and SW architects to co-design features and evaluate trade-offs across the stack.
Analyze bottlenecks and performance on workloads reflecting future AI use cases.
Provide proof-of-concept implementations for new architectural features and design alternatives.
Potentially lead feature definition in addition to the modeling role.

Our team at the Huawei Computing Network Innovation Lab is looking for exceptional talent to join us and lead the development of next-generation data centers. We create cutting-edge technologies that synergize software and hardware in tandem to accelerate compute, storage, and networking at large scale. We aim to drive innovation and deliver software-defined infrastructure and algorithms for HPC, AI/ML, and Big Data applications.
We are looking for an outstanding Research Team Lead with deep hands-on expertise in large-scale distributed systems, AI framework infrastructure, and performance optimization on custom accelerators. If you are a visionary technical leader, a skilled communicator, and a team builder who thrives at the frontier of systems and AI research - you're welcome on board.

What Will You Be Doing?
Lead and grow a world-class team of researchers and engineers working on distributed AI infrastructure and systems software.
Architect and own the software infrastructure enabling distributed training and inference on Huawei's custom accelerator hardware (e.g., Ascend NPU).
Drive research and development on communication libraries, runtime systems, memory management, and graph execution & synchronization at scale.
Optimize end-to-end performance across large-scale clusters, covering both scale-up (multi-device) and scale-out (multi-node) configurations.
Design and implement high-performance communication backends and collective operations (AllReduce, AllGather, broadcast) for distributed training workloads.
Collaborate cross-functionally with hardware architects, compiler teams, and framework engineers to co-design hardware-software solutions.
Publish and present research findings at top international venues (NeurIPS, EuroSys, SC, MLSys, OSDI) and represent the team externally.
Mentor engineers and researchers, conduct performance and growth reviews, and shape team culture and technical direction.
Partner with top academic institutions and open-source communities to advance the state of the art in distributed AI systems.

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.

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.

We are seeking a seasoned Sr Staff Physical Design Engineer to provide technical leadership across full-chip and multi-die physical implementation on advanced TSMC FinFET nodes. You will define and own the backend design methodology, champion Agentic AI integration into the PD flow, and mentor engineers across the team while interfacing directly with foundry, EDA vendors, and executive stakeholders.

What You'll Do
Architect and own the full-chip physical design strategy: floorplanning, power delivery network (PDN), clock architecture, PnR, and timing closure
Define and drive backend methodology standards across the team for advanced node tapeouts (N5/N4P/N3)
Lead critical timing closure efforts - MCMM, OCV, advanced ECO strategies, and cross-corner sign-off
Oversee and guide signal integrity, power integrity, EM/IR, and reliability analysis for full-chip designs
Architect and lead the development of scalable PD flow infrastructure using Python and TCL - including automated regression, sign-off reporting, and run management systems
Champion the adoption of Agentic AI in the design flow - define use cases, evaluate tools, prototype autonomous agents for floorplan exploration, timing closure, and ECO automation
Lead cross-functional design reviews with DFT, verification, analog, and process engineering teams
Interface with TSMC, EDA vendors (Synopsys, Cadence, Siemens), and internal research teams to evaluate and adopt new methodologies
Mentor and technically guide junior and mid-level PD engineers across the organization

The ATE Engineer is responsible for development of ATE test station development, including system architecture, test strategy, and transition from R&D to production. We are seeking a highly experienced professional with a strong background in RF, digital, and system-level testing, and with the ability to guide technical decisions, solve complex integration challenges, and support advanced test equipment for production environments.

What will you do:

Design and develop Automated Test Equipment (ATE) for RF, digital, and mixed-signal products at board and system levels.

Lead the technical definition and implementation of test strategies in collaboration with R&D, product engineering, and manufacturing teams.

Own the technical analysis of system schematics, block diagrams, and interface requirements to define robust and reliable ATE solutions.

Support production lines by troubleshooting test failures and optimizing test processes for yield and throughput improvements.

Provide technical guidance for integration with software and firmware control and automation systems.

Evaluate and select test instruments, fixtures, and measurement techniques based on product specifications.

Maintain documentation for test systems, including design files, calibration procedures, and troubleshooting guides.

Mentor engineers and technicians on ATE methodologies, operation, and maintenance.

Be part of a team responsible for designing the next generation of mobile devices. The position includes responsibility for system analysis and HW architecture design for high-speed and low-power interfaces, networking protocols, storage processing, including acceleration of protocols reducing overall power consumption. The job requires collaboration with multiple engineering functions and teams in various geographical locations. It includes identifying system use, requirements definitions, understanding of industry specification for interfaces, operating in industry Standards committees, SW and HW interaction, performance analysis, and more.

*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.