דרושים » חשמל ואלקטרוניקה » מהנדס /ת מעבדה במערכות מרובות רובוטים בפקולטה להנדסת חשמל ומחשבים, JB-2518

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.

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.

*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