דרושים » חשמל ואלקטרוניקה » Wafer-Scale System: Computation (LLM) and Communication (NoC) Co-Design

*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.

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.

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're looking for an exceptional senior Chip Design Engineer to join our Nitro team and help shape what comes next. You'll work alongside a world-class, fast-moving engineering team, take full ownership of critical IP blocks, and see your work deployed at a scale no other platform can match- powering hundreds of thousands of businesses across 190 countries.

As a Senior Chip Design Engineer on the Nitro team, you will take full end-to-end ownership of one or more critical IP blocks within the product, guiding them from micro-architecture definition through RTL design, debug, synthesis, timing closure, and final sign-off before tape-out. Your work will ship in silicon that powers AWS at global scale.
You'll partner closely with the Verification and Emulation teams to shape test plans, review coverage, and close gaps early in the design cycle. Beyond your own IP, you'll collaborate across disciplines with Product Definition, Software, Physical Design, and Verification teams to deliver a fully integrated, production-ready chip.

Key job responsibilities
* Full ownership of one or more IPs within the product:
Micro-architecture definition.
RTL coding and debug.
Synthesis and timing closure.
Sign-off before tape-out.
* Supporting the Verification and Emulation teams: Test plan development, coverage review.
* Ensuring the chip meets quality and reliability standards.
* Collaborating with cross-functional teams, including Product Definition, Verification, Software, and Physical Design.

Are you passionate about systems programming at the intersection of hardware and software? Do you want your code to directly accelerate the world's largest AI training and inference workloads? The Elastic Fabric Adapter (EFA) Drivers team is looking for Software Development Engineers to design and implement the kernel drivers and userspace libraries that power high-performance networking for AWS's AI/ML and HPC infrastructure.

EFA is the custom network interface that enables thousands of GPUs and accelerators to communicate at near-wire-speed bandwidth and low latency, making it a critical enabler of both foundation model training and real-time inference serving at unprecedented scale. When customers train the next generation of large language models or serve billions of inference requests with tight latency SLAs on our EC2 P5, P6, or Trn instances, it's our driver stack that moves the data.

Key job responsibilities
- Design, develop, and optimize Linux kernel drivers (RDMA/EFA) and userspace provider libraries (rdma-core) that ship to millions of EC2 instances.
- Work directly with custom hardware - collaborate with chip designers to bring new silicon capabilities to life in software.
- Contribute to the upstream Linux kernel RDMA subsystem and rdma-core open-source project.
- Architect solutions for next-generation networking features: GPU-direct RDMA, adaptive routing, collective offloads, and multi-path transport.
- Build monitoring and automation tools to enhance driver testing for functionality, reliability, and performance.
- Own the full lifecycle: from initial hardware bring-up and feature enablement through testing, deployment, and production troubleshooting across the global AWS fleet.

Required Silicon Test and DFT Engineer, Cloud
About the job
In this role, youll work to shape the future of AI/ML hardware acceleration. You will have an opportunity to drive cutting-edge TPU (Tensor Processing Unit) technology that powers our most demanding AI/ML applications. Youll be part of a team that pushes boundaries, developing custom silicon solutions that power the future of our TPU. You'll contribute to the innovation behind products loved by millions worldwide, and leverage your design and verification expertise to verify complex digital designs, with a specific focus on TPU architecture and its integration within AI/ML-driven systems.The AI and Infrastructure team is redefining whats possible. We empower customers with breakthrough capabilities and insights by delivering AI and Infrastructure at unparalleled scale, efficiency, reliability and velocity.
We're behind groundbreaking innovations, empowering the development of AI models, delivering unparalleled computing power to global services, and providing the essential platforms that enable developers to build the future. From software to hardware our teams are shaping the future of world-leading hyperscale computing, with key teams working on the development of our TPUs, Vertex AI for Cloud, Global Networking, Data Center operations, systems research, and much more.
Responsibilities
Collaborate with Architecture, Design and Verification teams to develop new product bring-up, validation, characterization, and qualification strategies and manufacturing test solutions for new High Performance Computing (HPC) products in advanced process technologies.
Verify test solutions on pre-silicon models (simulation or emulation) and develop Automated Test Equipment (ATE) test modules and binning flows.
Develop and validate test programs on Automated Test Equipment (ATE) platforms for new product integration (NPI) in preparation for high-volume manufacturing (HVM), working with ATE vendors and internal cross-functional teams.
Manage product sustainment support, including analyzing volume data, improving test time and yield, assessing test escapees and return merchandise authorizations (RMAs), localizing failures, implementing containment measures, and partnering with design, manufacturing, and quality and reliability teams to identify root causes and implement corrective actions.
Build tools, flows and methodologies to continuously improve and automate the testing life-cycle.

We are looking for a junior Embedded Software Engineer, to join us in building the next generation of networking products. Youll have the opportunity to work on the technologies that power the worlds largest cloud provider, in a dynamic, open, fast-paced environment. Working for Annapurna Labs is thrilling and a constant learning experience. As an embedded SW development engineer, you will be responsible for developing features for Annapurna Labs next-generation hardware, to enable high network bandwidth and packets-per-seconds (PPS) performance, with consistently low latency. You will work to bring up a broad selection of instance types, optimized for various use cases, to suit each of our customers needs, such as varying combinations of CPU, memory, storage, and networking capabilities. As a SW development engineer, you will play a key role in shaping architecture definitions and SW system designs, and help to resolve complex customer issues. You will continuously evolve technically, while working to monitor AWS cloud health, maintain high quality standards, develop highly-optimized code, and provide exceptional customer satisfaction.

Key job responsibilities
We will be conducting a unique onboarding training program, where you will be studying the following with our technical experts and team leaders:
* Embedded systems basics.
* Annapurna technologies in EC2.
* Cloud compute development.
* Networking 101.

As a leading technology innovator, we push the boundaries of what's possible to enable next-generation experiences and drive digital transformation, creating a smarter, connected future for all.

As a company AI Software Engineer, you will develop and implement cutting-edge AI techniques that enable the efficient utilization of state-of-the-art solutions across various technology verticals.

In this position, you will be responsible for leading software development and implementation of the company AI Stack features within our AI Runtime (QAIRT) SDK, specifically Core software including Generative AI Inference Extensions. You will contribute to the efficient execution of advanced deep neural networks (DNNs), large language models (LLMs), and other modern AI architectures. You will also be responsible for supporting AI stack that optimizes runtime efficiency, latency and power consumption of AI applications running Machine Learning workloads on our low-power AI accelerators. The DSP core design work directly supports our NPU and GPU solutions, enabling optimized inference across diverse hardware platforms.

You will have the opportunity to demonstrate your passion for software design and development through your analytical, design, programming, and debugging skills.
Responsibilities
Develop real-time software for our AI DSPs to support the execution of the latest generative AI models on Snapdragon platforms

Develop and implement core components of our AI Stack runtime framework for inference on resource constrained AI systems, operating in low power, small memory footprint platforms

Validate, analyze, and optimize the performance and accuracy of software through detailed testing of machine learning use cases

Debug complex issues, perform root cause analysis, and ensure high system reliability

Collaborate with cross-functional teams to deliver robust, scalable AI software solutions

Contribute to a culture of technical excellence, knowledge sharing, and continuous improvement within the AI Software team

Participate in design and code reviews

Working in global environment and collaborating inside the team and across other AI teams

We are looking for exceptional engineers to join the top-tier team developing the next generation semiconductor platform based on a revolutionary architecture. You will participate in design activities, working on the next generation of our products.

As a Chip Design Engineer and a member of the Nitro project, you will have an impact over the device through its entire lifecycle, from the product definition stage to mass production. You will work in close collaboration with multiple groups, including Architecture, Software, Verification, Backend, and DFT.

Key job responsibilities:
* Full ownership of one or more IPs within the product:
-Micro-architecture.
-RTL coding and debug.
-Synthesis and timing closure.
-Sign-off.
* Supporting the Verification and Emulation teams: Test plan, Coverage review.
* Ensuring that the chip meets quality and reliability standards.
* Collaborating with cross-functional teams, including Product Definition, Verification, Software, and Physical design.

Required RTL Design Technical Lead, Networking, Cloud
About the job
Be part of a team that pushes boundaries, developing custom silicon solutions that power the future of our direct-to-consumer products. You'll contribute to the innovation behind products loved by millions worldwide. Your expertise will shape the next generation of hardware experiences, delivering unparalleled performance, efficiency, and integration.
As part of our Server Chip Design team, you will use your ASIC design experience to be part of a team that creates the SoC VLSI design cycle from start to finish. You will collaborate closely with design and verification engineers in active projects, creating architecture definitions with RTL coding, and running block level simulations.
In this role, you will contribute in all phases of Application-Specific Integrated Circuit (ASIC) designs from design specification to production. You will collaborate with members of architecture, software, verification, power, timing, synthesis, etc. to specify and deliver high quality SoC/RTL. You will solve technical problems with innovative micro-architecture and practical logic solutions, and evaluate design options with complexity, performance, power and area in mind.
We prioritize security, efficiency, and reliability across everything we do - from developing our latest TPUs to running a global network, while driving towards shaping the future of hyperscale computing. Our global impact spans software and hardware, including Clouds Vertex AI, the leading AI platform for bringing Gemini models to enterprise customers.
Responsibilities
Define the block level design documents such as interface protocol, block diagram, transaction flow, pipeline, and more.
Perform RTL development (e.g., coding and debug in Verilog, SystemVerilog, VHDL), function/performance simulation debug, and Lint/CDC/FV/UPF checks.
Participate in synthesis, timing/power, and FPGA/silicon bring-up.
Participate in test plan and coverage analysis of the block and SOC-level verification.
Communicate and work with multi-disciplined and multi-site teams.