Role at a glance
- Salary
- $143.7K – $194.4K/yr
- Location
- Seattle, Washington, United States
- Work arrangement
- On-site
- Employment
- Internship
- Experience
- 3+ years of non-internship professional software development experience
- Education
- Bachelor's degree in computer science or equivalent
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Role Summary
The EC2 Nitro Machine Learning Systems team is developing and operating scale-out machine learning platforms for training and inference workloads. This role builds performance measurement infrastructure for AI/ML workloads and translates performance findings from research and customer workloads into requirements and recommendations for future accelerated platform designs.
What You'll Do
- Design and build foundational infrastructure for ML performance measurement that operates as reliable CI/CD systems.
- Develop regression test coverage across frameworks, firmware, drivers, and networking technologies.
- Establish EC2 as the definitive source for best-known-configurations across LLMs, multimodal models, and MoE architectures.
- Document and communicate performance insights as actionable recommendations for future platform designs.
- Analyze training and inference performance KPIs across accelerated platforms and resolve complex performance challenges with customers.
Generated from the employer's posting. Verify important details before applying.
View full postingQualifications
Required
- 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
- Knowledge of Machine Learning and LLM fundamentals, including transformer architecture, training/inference lifecycles, and optimization techniques
Preferred
- 3+ 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
Original job description
Content provided by the employer
Original job description
Content provided by the employer
Your impact will extend from low-level systems (CUDA, EFA, firmware) through ML frameworks to serving layers, requiring deep technical knowledge and the ability to communicate complex performance data as actionable business insights. This position offers the unique opportunity to shape the future of machine learning infrastructure at cloud scale while working at the intersection of high-performance computing, distributed systems, and machine learning technologies.
Key job responsibilities
- Design and build foundational infrastructure for ML performance measurement that scales with business demand and operates as reliable CI/CD systems, ensuring high-quality implementations that balance customer requirements with operational excellence
- Develop comprehensive regression test coverage across all major component releases including frameworks, firmware, drivers, and networking technologies to maintain optimal platform performance
- Collaborate with cross-functional teams to establish EC2 as the definitive source for best-known-configurations across diverse ML applications including LLMs, multimodal models, and MoE architectures
- Document and communicate performance insights to influence future platform designs by translating technical findings from research and customer workloads into actionable recommendations
- Identify and resolve complex performance challenges through systematic analysis of training and inference performance KPIs across accelerated platforms, working directly with customers to improve their ML system efficiency
A day in the life
Your typical day begins with reviewing performance data from overnight benchmark runs across various ML frameworks and hardware configurations. You'll investigate anomalies, collaborate with the team on optimization opportunities, and join design reviews to influence future platform capabilities. You'll balance your time between building measurement infrastructure, analyzing performance trends, and documenting best practices to help customers optimize their workloads.
About the team
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.
Basic Qualifications
- 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
- Knowledge of Machine Learning and LLM fundamentals, including transformer architecture, training/inference lifecycles, and optimization techniques
Preferred Qualifications
- 3+ 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.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
USA, WA, Seattle - 143,700.00 - 194,400.00 USD annually
About the company
amazon
Large Enterprise
Amazon is a global leader in e-commerce and cloud computing, founded in 1994 by Jeff Bezos. Initially starting as an online bookstore, it has since expanded its offerings to include a vast range of products and services, including electronics, fashion, and digital content. With Amazon Web Services (AWS), the company also provides powerful cloud solutions to businesses around the world. Known for its innovation, customer-centric approach, and commitment to operational efficiency, Amazon continues to shape the future of retail and technology, consistently seeking new ways to enhance customer experiences.
Amazon is a global leader in e-commerce and cloud computing, founded in 1994 by Jeff Bezos. Initially starting as an online bookstore, it has since expanded its offerings to include a vast range of products and services, including electronics, fashion, and digital content. With Amazon Web Services (AWS), the company also provides powerful cloud solutions to businesses around the world. Known for its innovation, customer-centric approach, and commitment to operational efficiency, Amazon continues to shape the future of retail and technology, consistently seeking new ways to enhance customer experiences.