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The role
We are looking for a Software Development Engineer who is a pragmatic problem solver, comfortable with ambiguity, and curious about applied science. You will build and improve the Search Navigation platform, including the systems that serve LLMs in real time, and work closely with Applied Scientists to take new models from research into production.
Design, build, and operate large-scale, distributed, low-latency services that power Amazon Search Navigation experiences worldwide
Build and optimize online LLM serving for Smart Refinement and multi-turn conversational refinement, with a focus on latency, reliability, and costWork with Applied Scientists, Product Managers, and Program Managers to define requirements and integrate models into production systemsBuild scalable data pipelines that process large volumes of search and behavioral data for feature generation, model training, and evaluationDesign, run, and analyze online A/B experiments to measure the impact of new models and featuresContribute to operational excellence for critical services, including monitoring, on-call, and P0 metrics and defect guardrailsWrite high-quality, well-tested code and take part in design and code reviews3+ years of non-internship professional software development experience3+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience3+ years of software development engineer or related occupational experience3+ years of designing and developing large-scale, multi-tiered, multi-threaded, embedded or distributed software applications, tools, systems, and services using: C#, C++, Java, or Perl experience3+ years of Object Oriented Design experienceExperience programming with at least one software programming languageBachelor's degree in computer science or equivalentExperience in developing and deploying LLMs in production on GPUs, Neuron, TPU or other AI acceleration hardwareExperience in machine learning, data mining, information retrieval, statistics or natural language processingExperience with Machine Learning and Large Language Model fundamentals, including architecture, training/inference lifecycles, and optimization of model executionOur 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.
USA, WA, Seattle – 143,700.00 - 194,400.00 USD annually
About Amazon.com Services LLC
The Amazon Search Navigation AI team helps customers go from a broad search intent to the few products that fit their needs, so they can make a confident purchase decision. We generate highly relevant, context-aware, and personalized search refinements. We also decide the order they appear in across Amazon's Search Navigation experiences, guiding customers to the most relevant results. The team owns Search Navigation's P0 metrics and defect guardrails, which keep performance and reliability high for hundreds of millions of customers.
We are reinventing search refinement with generative AI. Our recently launched Smart Refinement experience uses large language models (LLMs) served online to turn product specifications into natural-language suggestions that match how customers think, such as "for colder weather" or "lightweight for travel." Each suggestion is personalized to the customer's context. Next, we are building multi-turn, conversational refinement, where each interaction builds on the last and helps customers narrow their intent in fewer steps.
We build and run the engineering systems behind this work, including the Navigation Experience Service (NES). NES connects to Amazon's core search systems, serves more than 3 billion queries worldwide every day, and runs real-time LLM inference at global scale under strict latency and cost limits. Our platform supports launches of new navigation content and UIs, and it makes fast offline and online experimentation possible.
Legal notes
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
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