Software Engineer- AI​/ML, AWS Neuron Distributed Training - Optimization

Overview

Annapurna Labs designs silicon and software that accelerates innovation. Customers choose us to create cloud solutions that solve challenges that were unimaginable a short time ago—even yesterday. Our custom chips, accelerators, and software stacks enable us to take on technical challenges that have never been seen before, and deliver results that help our customers change the world.

AWS Neuron is the complete software stack for the AWS Trainium and Inferentia cloud‑scale machine learning accelerators and the Trn3/Trn2/Trn1 and Inf2/Inf1 servers that use them. This role is for a software engineer in the Distributed Training team for AWS Neuron, responsible for development, enablement and performance tuning of a wide variety of ML model families, including massive scale multi‑modal large language models like Llama, Qwen, gpt‑oss, Deep Seek and beyond, as well as multi‑modal generation models such as Stable Diffusion, Flux, WAN, and many more.

• Lead efforts to optimize distributed training performance on Trainium, focusing on maximizing training throughput, model FLOPs utilization, and efficiency across the Neuron software stack.
• Identify and resolve performance bottlenecks across the stack, from collective communications and memory utilization to compiler optimizations and kernel performance.
• Work across PyTorch, JAX, and the Neuron compiler and runtime to enable and tune large‑scale training workloads on the latest Trainium instances.

• 3+ years of non‑internship professional software development experience.
• 2+ years of non‑internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience.
• Experience programming with at least one software programming language.

• 3+ years of full software development life cycle experience, including coding standards, code reviews, source control management, build processes, testing, and operations experience.
• Bachelor’s degree in computer science or equivalent.

USA, WA, Seattle - $ - $ USD annually

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