Senior Machine Learning Engineer, Sponsored Products and Brands Relevance

Amazon • Palo Alto, CA

3d • $193,300 - $261,500 • Onsite

About The Position

Build the ML systems that decide which ads billions of shoppers see every day — the SPB Relevance team owns ad selection across one of the world's largest product catalogs, matching customer intent to relevant ads in milliseconds at Amazon scale. As a Senior MLE, you'll drive the technical direction of real-time ML serving systems that process billions of daily requests under strict latency SLAs, while mentoring engineers and shaping the future of ad relevance on Amazon Search. You'll work at the intersection of deep learning, NLP, LLMs, and distributed systems — directly impacting both shopper experience and advertiser ROI.

Amazon Advertising is one of Amazon's fastest growing and most profitable businesses. Sponsored Products and Brands (SPB) helps merchants, retail vendors, and brand owners succeed via native advertising that drives incremental sales. We deliver billions of ad impressions and millions of clicks daily, breaking fresh ground in product and technical innovation.

The SPB Relevance team identifies the most relevant ads to surface when customers search for products on Amazon. We strive to understand customer intent and surface ads that help shoppers discover new and alternate products — while enabling sellers to showcase products that might otherwise be buried in search results.

Our systems operate on one of the world's largest product catalogs with a high relevance bar and strict latency constraints. We are a team of machine learning scientists and engineers building complex solutions to understand customer intent and present ads that are relevant to the shopping experience and non-obtrusive. This area is of strategic importance to Amazon's Retail and Marketplace businesses, driving long-term growth.

A day in the life
You'll spend your time designing and building ML systems that determine ad relevance for billions of search queries. You'll collaborate with applied scientists on model optimization, make architectural decisions for distributed serving infrastructure, and mentor engineers on your team. You'll operate on massive datasets using distributed frameworks, balancing innovation with the operational rigor required for systems that directly impact Amazon's customer experience and advertising revenue.

About the team
The Sponsored Products and Brands Relevance team at Amazon Ads is re-imagining the advertising landscape through industry leading generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights. We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising.

Requirements

• 8+ years of non-internship professional software development experience
• 10+ 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 building large-scale machine-learning infrastructure for online recommendation, ads ranking, personalization or search experience
• Demonstrated ability to drive technical decisions across teams and deliver end-to-end from design through production deployment

Nice To Haves

• 10+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
• Master's degree in computer science or equivalent
• Experience with model serving infrastructure (SageMaker, Triton, vLLM, or equivalent)
• Experience with LLM/GenAI systems in production — such as prompt engineering, fine-tuning, retrieval-augmented generation, or agentic workflows
• Hands-on experience with ML frameworks such as PyTorch or TensorFlow
• Experience with large-scale data processing using Spark

Responsibilities

• Drive the technical direction of ML solutions across deep learning, AWS infrastructure, Auto ML, and real-time serving systems
• Design, develop, and own scalable offline ML pipelines and online serving components that handle billions of requests per day at millisecond latency
• Partner closely with applied scientists to optimize model performance, improve ML productivity, and advance the technical foundation that powers science innovation
• Troubleshoot and support high-volume, low-latency distributed systems — what you build is what you own
• Mentor junior engineers and guide them to deliver high-impact products and services for Amazon customers and sellers
• Make appropriate technology choices that balance innovation velocity with operational excellence and business needs

Benefits

• sign-on payments
• restricted stock units (RSUs)
• 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
• parental leave

What This Job Offers

• Job Type: Full-time
• Career Level: Senior