Software Dev Engineer II, Stores Foundational AI -SFAI

Amazon Inc.; Seattle (WA); On-site; USD 144,000 - 194,000; Full time

Benefits offered by this job

Sign-on bonuses

RSUs

Comprehensive benefits

Health insurance

Job summary

Amazon is seeking a Software Dev Engineer II for Stores Foundational AI (SFAI) to design scalable training systems and data pipelines for large language models and reinforcement learning across model families. You will work with researchers and engineers to push the frontend of AI tooling and model training at scale.

You will contribute to production-grade systems, optimize training performance, and help build observability into training dynamics to support customer-facing AI capabilities.

Qualifications

• 3+ years of non‑internship professional software development experience.
• 2+ years of non‑internship design or architecture experience of new and existing systems.

Responsibilities

• Design and implementation of a stable and efficient training system for model training and reinforcement learning that scale to various model sizes and architectures.
• Collaborate with other scientists and engineers to improve training efficiency and reliability that accelerates innovation.
• Design and implement scalable data infrastructure to handle large-scale data ingestion, processing, and delivery across training and evaluation stages.
• Learn and adopt state-of-the-art technologies and algorithms in Generative AI.

Skills

Software development

System design

Machine learning fundamentals

CUDA/C++ development

Education

Bachelor's degree in Computer Science or related field

Tools

JAX

PyTorch

vLLM

SGLang

Dynamo

TorchXLA

TensorRT

Job description

Software Dev Engineer II, Stores Foundational AI -SFAI

ID lavoro: 10444927 | Amazon.com Services LLC

We’re working to improve shopping on Amazon using the capabilities of large language models (LLM), and are searching for pioneers who are passionate about technology, innovation, and customer experience, and are ready to make a lasting impact on the industry.

You’ll be working with talented scientists and engineers to innovate on behalf of our customers. If you're fired up about being part of a dynamic, driven team, then this is your moment to join us on this exciting journey!

Key job responsibilities

• Design and implementation of a stable and efficient training system for model training and reinforcement learning that scale to various of model sizes and architecture.
• Collaborate with other talented applied scientists and engineers to improve training efficiency and reliability that accelerates innovation.
• Design and implement scalable data infrastructure: that handle Amazon-scale data ingestion, processing, and delivery across different training and evaluation stages;
• Quickly learn and adopt state-of-the-art technologies and algorithms in the field of Generative AI.

Key job responsibilities

• Design and implementation of a stable and efficient training system for model training and reinforcement learning that scale to various of model sizes and architecture.
• Collaborate with other talented applied scientists and engineers to improve training efficiency and reliability that accelerates innovation.
• Design and implement scalable data infrastructure: that handle Amazon-scale data ingestion, processing, and delivery across different training and evaluation stages;
• Quickly learn and adopt state-of-the-art technologies and algorithms in the field of Generative AI.

A day in the life

• Design and build end-to-end RL post-training pipelines (rollout → reward → optimization) at cluster scale
• Improve RL training stability (PPO / GRPO / RLOO) by monitoring and tuning key metrics such as reward, KL divergence, and policy stability
• Optimize RL post-training efficiency (GPU utilization, batching, sequence packing, async rollouts)
• Partner with research scientists to translate new RL algorithms into scalable, production-ready systems
• Profile and eliminate bottlenecks across compute, networking, and storage
• Build observability systems for training dynamics, system health, and experiment tracking
• Collaborate cross-functionally to run experiments, iterate quickly, and unblock research progress
• Contribute to system design and long‑term technical roadmap

About the team

The SFAI Training Infrastructure team builds a unified platform for large‑scale LLM training, supporting the full lifecycle from pretraining to fine‑tuning and RL post‑training. We focus on solving hard system challenges at the intersection of distributed systems and machine learning, building a platform that is:

• Scalable — Efficiently train modern model architectures across large‑scale compute environments
• Reliable — Enable long‑running jobs through fault tolerance, monitoring, and automated recovery
• Efficient — Maximize hardware utilization and throughput through system‑level optimizations
• Simple and Unified — Provide a consistent, config‑driven interface across models and workflows

• 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

• Knowledge of ML frameworks including JAX, PyTorch, vLLM, SGLang, Dynamo, TorchXLA, and TensorRT
• Knowledge of system performance, memory management, and parallel computing principles
• Experience with CUDA/C++/Kernel development

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.

Qualifiche Preferenziali

• Knowledge of ML frameworks including JAX, PyTorch, vLLM, SGLang, Dynamo, TorchXLA, and TensorRT
• Knowledge of system performance, memory management, and parallel computing principles
• Experience with CUDA/C++/Kernel development

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 .

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