דרושים » הנדסה » Research Team Lead - Distributed AI Systems & Large-Scale Infrastructure

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.

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.

*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

Required Staff Embedded Firmware Engineer, High Speed DSP
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.
As a Staff Embedded Firmware Engineer for High-Speed DSP, you will architect and define the low-level firmware and control loops powering the world's most advanced physical-layer communications silicon. Sitting at the critical intersection of digital signal processing (DSP), hardware-software co-design, and real-time systems, you will lead the development of adaptive algorithms, error correction (FEC), and link-telemetry frameworks. Your work will directly bridge the gap between high-performance hardware pipelines and our planetary-scale AI infrastructure, transforming complex communication systems theory into reliable, real-time silicon execution.
Responsibilities
Define the long-term firmware roadmap and hardware-software partitioning for physical-layer interfaces, determining the optimal balance between hardware-fixed logic and programmable firmwarm.
Architect advanced "in-situ" monitoring systems and firmware-driven diagnostics to track physical-layer link health, Bit Error Rate (BER) trends, and channel quality across millions of ports in real-time.
Design, model, and implement bare-metal or RTOS firmware to control high-speed transceivers, managing real-time adaptive loops, clock and data recovery (CDR), and physical-layer calibration.
Partner with TPU Systems, Networking Software, and High-Performance Computing (HPC) teams to ensure silicon firmware integrates seamlessly with global cluster management and collective communication frameworks.
Identify and de-risk hardware-software interface bottlenecks (e.g., register maps, driver latencies, and boot-up sequencing) that impact our AI infrastructure.

We are looking for an experienced Software Team Leader to build and lead a new team focused on AI and agent technologies for enterprise data platforms.
This is a hands-on leadership role. The Team Leader will define the technical direction, build the first solutions, recruit engineers, and turn new AI ideas into production systems.
The main focus is AI agents, RAG, natural-language interaction, model integration, and intelligent workflows. Database technologies are an important foundation, but not the center of the role.

Responsibilities
Lead a new software engineering team.
Define the AI architecture, roadmap, and technical priorities.
Build AI agents that reason, use tools, and execute multi-step workflows.
Develop agent orchestration, state management, and workflow execution.
Build agent workflows for data analysis, automation, and decision support.
Integrate LLMs, embedding models, and model-serving platforms.
Develop tool and API integration for AI agents, including MCP where relevant.
Optimize AI systems for latency, throughput, cost, and scale.
Move successful prototypes into production-grade software.
Work closely with data, database, infrastructure, cloud, and product teams.

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.

Required Research Software Engineer
About the job
Our software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to our needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward. We're reimagining what it means to search for information - any way and anywhere. To do that, we need to solve complex engineering challenges and expand our infrastructure, while maintaining a universally accessible and useful experience that people around the world rely on. In joining the Search team, you'll have an opportunity to make an impact on billions of people globally.
Responsibilities
Write product or system development code.
Collaborate with peers and stakeholders through design and code reviews to ensure best practices amongst available technologies (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.
Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.
Implement solutions in one or more specialized ML areas, utilize ML infrastructure, and contribute to model optimization and data processing.

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 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

Required Micro-Architect, 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.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 our 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
Lead Design Activities at IPs, SubSystems(S.S) and SoC.
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, as well as test plan development and coverage analysis for block and SOC-level verification.
Communicate and collaborate with multi-disciplined and multi-site teams.