Senior Software Dev Engineer, EC2 Nitro

About the role

The EC2 Nitro Machine Learning Systems team is responsible for development, operations, and maintenance of scale-out machine learning platforms used for training and inference workloads. We build and optimize the infrastructure that powers some of the most computationally intensive AI/ML workloads in the cloud. Our team is passionate about creating reliable, high-performance systems that enable customers to push the boundaries of what's possible with machine learning. Working with us means having the opportunity to influence the future of supercomputing in the cloud while solving complex technical challenges at massive scale. We collaborate closely with customers and internal teams to continuously improve our platforms and deliver innovations that accelerate machine learning workflows.

Requirements

• 5+ years of non-internship professional software development experience
• 5+ years of programming with at least one software programming language experience
• 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience
• Experience as a mentor, tech lead or leading an engineering team
• Knowledge of Machine Learning and LLM fundamentals, including transformer architecture, training/inference lifecycles, and optimization techniques
• 5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
• Bachelor's degree in computer science or equivalent
• Knowledge of ML frameworks including JAX, PyTorch, vLLM, SGLang, Dynamo, TorchXLA, and TensorRT
• Knowledge of machine learning model architecture and inference
• Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Additional Information

Join the EC2 Nitro Machine Learning Systems team to revolutionize supercomputing in the cloud. We're seeking an experienced Software Development Engineer to build and optimize infrastructure powering the most computationally intensive AI/ML workloads. In this role, you'll establish EC2 as the definitive source for best-known-configurations across diverse ML applications while influencing future accelerated platform designs. You'll bring deep expertise in ML systems performance, working across the full stack from low-level hardware optimization to high-level frameworks. This position offers unique opportunities to translate state of the art ML research into practical platform improvements, build foundational measurement infrastructure, and directly support customers with performance challenges. If you're passionate about solving complex performance optimization problems at massive scale while directly influencing product strategy, this role provides the perfect opportunity to make a significant impact. Key job responsibilities - Design and implement scalable performance measurement infrastructure that serves as the foundation for ML benchmarking across AWS, incorporating critical metrics like tokens/second, latency, and accelerator utilization - Lead technical projects establishing EC2 as the definitive source for ML performance best practices across diverse applications including LLMs, multimodal systems, and emerging model architectures - Develop and maintain comprehensive regression testing systems that validate performance across major component releases including frameworks, firmware, drivers, and networking infrastructure - Collaborate with hardware engineering teams to influence future accelerator platform designs based on performance insights gathered from state-of-the-art research and customer workloads - Build customer relationships by investigating complex performance challenges, developing solutions, and publishing actionable best practices through multiple channels A day in the life Your day revolves around translating technical performance data into actionable business insights while solving complex optimization challenges. You might start by analyzing performance bottlenecks in a customer's large language model training workflow, then collaborate with framework engineers to implement optimizations. Later, you'll present findings at a platform design review, where your data-driven insights directly influence future hardware decisions. Throughout the day, you'll balance immediate customer needs with long-term infrastructure development, all while helping establish processes for this bootstrap team.

Your Match

How well this role fits your profile.

Company Intel

What employees say

Worked at Amazon Development Center U.S., Inc.? Share your experience