Amazon Search creates powerful, customer-focused product search solutions and technologies. Whenever a customer visits an Amazon site worldwide and types in a query or browses through product categories, our systems go to work. We delight customers when we accurately understand their intent expressed via a query or image, and reflect that understanding throughout the search page - from layout to the search results and navigation. We make shopping effortless by helping customers easily explore our vast selection, narrowing down a myriad of options to a manageable consideration set while providing key information to make high confidence decisions with low post-purchase regret

Search Science Data Infrastructure team is responsible for delivering high quality and fresh ML model training data, and providing seamless access to all ML artifacts through federated Feature Store infrastructure. This big-data platform provides the ML training data to Amazon search ranking, matching quality, search economics and also powers live-site features, including search suggestions, query understanding, spelling, search result ranking, and personalization. Furthermore, 350+ teams across Amazon consume our datasets to power analytics and behavior models. We are located in downtown Palo Alto, a short walk from numerous shops and restaurants, and right across from the Caltrain station.

Key job responsibilities
As ML Engineer you will:
Develop services and infrastructure at the intersection of machine learning, big data, and distributed systems. Our products and services empower hundreds of science teams across Amazon to deliver machine learning at scale for ML model training, Feature engineering and Data quality monitoring. You will be responsible for managing machine learning lifecycle and operations using AWS AI services, DL compute resources, and our core search backend services for query understanding, semantic matching, and relevance ranking. You will contribute to provide a world class platform for Amazon Search engineers to comprehensively observe and introspect their applications and services both pre and post deployment to our large scale inference services. You will build scalable data-intensive infrastructure that processes huge amounts of logs, catalogs, transactional data, and telemetry signals. By doing so, we enable teams to become more data-driven and build robust and explainable ML services. You will work with partners on data experimentation to advance Amazon product search, making it available across all geographic regions with variety of product search and discovery use cases across many categories.

Design & Develop

• Lead the design, get your hands dirty and write code, and ultimately deploy big data and machine learning services. These services define the foundation of our search R&D processes, supporting science, product development and production of the world’s largest product search engine.
• Possess knowledge in performance, large scale distributed system scalability, system architecture, and engineering best practices.

Operational Excellence

• Obsess over operational excellence, evaluate system performance, security, design system metrics and driving quality improvements
• Obsess over customer needs and satisfaction

• Graduate degree in computer science or related field (MS or Ph.D.)
• Data-driven and quantitative mindset. Grounded, detail-oriented, always backs up ideas with facts
• Ability to understand complex application data flows and bridge the gap between technical and business app requirement
• Track record of implementing AWS services in a variety of business such as large enterprises and start-ups
• 3+ years hands-on experience as ML Engineer on multiple software engineering or Machine Learning projects
• Experience in Search Engine development, ML inference pipeline, Model performance optimization, Model quality monitoring etc.

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $115,000/year in our lowest geographic market up to $223,600/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. Applicants should apply via our internal or external career site.