Embedded Software Engineer, Linux Kernel

- Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field
- 3+ years of non-internship professional software development experience in C/C++
- Experience contributing to the architecture and design (architecture, design patterns, reliability and scaling) of new and current systems
- 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
- Experience in debugging, profiling, and implementing software engineering best practices in large-scale systems
- Experience writing low level drivers
- Experience with DMA, PCIe, or hardware/software co-design
- Contributions to open-source projects or upstream kernel work

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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 Amazon 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