Sr. Software Development Engineer – AI/ML Networking Disaggregated Inference, Annapurna Labs, Annapurna Labs

Every token a large language model generates depends on data reaching the right accelerator at the right moment. As AI models outgrow any single chip, the network between accelerators becomes the bottleneck that decides how fast — and how affordably — the world's largest models can serve real users. That network layer is what our team builds. We're looking for an engineer to work at the frontier of disaggregated inference: splitting LLM serving into separate prefill and decode pools and moving the model's KV cache between them at the absolute limit of what the hardware allows. Get it right and users get answers in milliseconds; get it wrong and the fastest accelerators in the world sit idle waiting on data. You'll own pieces of the high-speed transfer path that make the difference, and you'll measure your success in how close you run to the theoretical peak of the machine. In this role you will: Build and optimize the low-level data-movement software across accelerators, servers, and heterogeneous memory — over AWS's highest-performance network fabric. Push performance to the hardware roofline: profile, find the real bottleneck, and close the gap between "it works" and "it runs as fast as physics permits." Work across the stack — from kernel and network transport up to the inference frameworks — and partner with teams building the chips, runtime, and models. Deliver features that run on our largest clusters, for our largest customers, serving the largest AI models in production.

Strong C/C++ and a love for low-level, performance-critical systems — solid command of Linux, kernels, memory, and writing fast code. The instinct to ask "how fast could this possibly go?" and the rigor to measure it. Experience with high-speed networking or HPC interconnects (RDMA, InfiniBand, libfabric, UCX, NIXL, MPI) is valued highly; embedded-systems experience is a plus. Prior AI/ML experience is welcome but not required — if you're a great systems engineer, we'll teach you the ML side. If you like solving genuinely hard problems, working shoulder-to-shoulder with HPC and ML customers, iterating fast, and shipping at a scale few places can offer, come join us. This is a role on the leading edge of AI/ML infrastructure.

You'd be joining Annapurna Labs, an integral part of AWS. Annapurna designs the hardware and software building blocks behind EC2 — every EC2 instance runs on hardware we designed. We specialize in the chips, systems, and software that optimize the AWS customer experience, and this team sits where cutting-edge AI meets the silicon and the network underneath it. A day in the life Annapurna Labs, a crucial part of AWS, is responsible for developing hardware and software components for EC2 infrastructure. Our team focuses on building networking solutions that for Machine Learning (ML) and High-Performance Computing (HPC) workloads on AWS. We have mixed discipline orgs, you’d be working side by side with infrastructure experts, hardware engineers, RTL engineers, scientists & architects. Our workforce spans the globe and is truly international, you’ll find yourself working side by side with individuals from numerous countries. We take mentorship seriously, you can both expect senior mentorship and will be expected to mentor new and junior engineers. The pace is fast as we work on the latest advancements of AI/ML, but we take the time to bond as a team and enjoy the successes. We offer flexibility in working hours, and respect WLB as a core org tenet. The team enjoys working with numerous principal-level engineers and closely with directors, career growth opportunities are certainly available. This is a role where you will always be encouraged to keep learning, the AI/ML field is fast moving and constantly evolving.