Amazon.com Services LLC

Technology

SoftwareDevelopmentEngineerII,ItemsandRelationshipsPlatform

$70–194k Seattle, Washington, United States FULL TIME
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Mid candidates.

The Brief

“Software Development Engineer II, Items and Relationships Platform at Amazon.com Services LLC. Skills: GenAI, ML platforms, Distributed systems. Build GenAI serving systems. Optimize GenAI serving systems”

What You'll Achieve.

Reduce latency and cost; Achieve order-of-magnitude cost reductions; Accelerate experiment speed; Serve frontier models efficiently; Serve hundreds of millions customers daily; Accelerate research ideas to production

Industry & Context.

Technology
Problems you'll solve

Tackle hard problems; Reason over complex data

What They're Looking For.

Must Have

3+ years software development experience, 2+ years system design experience, Experience programming one language

Nice to Have

3+ years full SDLC experience, Bachelor's degree computer science, Experience building complex software systems, Machine Learning fundamentals, Large Language Model fundamentals, vLLM production experience, SGLang production experience, TensorRT production experience, Large-scale data systems experience, Vector databases experience, Approximate nearest neighbor search experience, CI/CD pipelines experience, Workflow orchestration experience, ML workflow automation experience

What You'll Do.

Build GenAI serving systems

Optimize GenAI serving systems

Build agentic systems

Automate training pipelines

Curate data intelligently

Improve models continuously

Develop evaluation frameworks

Implement CI/CD for workflows

Architect distributed systems

Ensure high availability

Achieve operational excellence

Productionize research

Bridge research and infrastructure

Generate intellectual property

Contribute novel designs

Drive engineering excellence

Perform rigorous code reviews

Design scalable systems

Conduct comprehensive testing

Maintain proactive ownership

Mentor junior engineers

How You'll Work.

Team & Collaboration

Partner with applied scientists

Full Job Description

At Amazon Selection and Catalog Systems (ASCS), our mission is to power the online buying experience for customers worldwide so they can find, discover, and buy any product they want. We innovate on behalf of our customers to ensure uniqueness and consistency of product identity and to infer relationships between products in Amazon's Catalog to drive the selection gateway for the search and browse experiences on the website. We're solving a fundamental AI challenge: establishing product identity and relationships. Using Generative AI, Visual Language Models (VLMs), and multimodal reasoning, we determine what makes each product unique and how products relate to one another across Amazon's catalog. The scale is staggering: billions of products, petabytes of multimodal data, millions of sellers, dozens of languages, and infinite product diversity—from electronics to groceries to digital content. The PRISM team operates at the frontier of ML engineering. We build the serving infrastructure and ML platforms that bring large-scale GenAI—LLMs, VLMs, multimodal foundation models—from research to production across Amazon's catalog. You'll work with the latest techniques in optimized model serving, distillation, quantization, distributed inference, querying billion-scale vector indices, and agentic systems that automate data curation, training, and evaluation end-to-end. Every system you build accelerates how fast we can experiment and how efficiently we can serve frontier models to hundreds of millions of customers daily. We are looking for a Software Development Engineer at the intersection of GenAI, ML platforms, and high-scale distributed systems. You will tackle some of the hardest problems in ML engineering—optimizing LLM/VLM serving for latency and cost at massive scale, designing agentic systems that autonomously reason over complex product data, and building the automated pipelines that continuously integrate, test, and deploy models into production. Working alongsid

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