Amazon

Applied Scientist II role at Amazon Ads focusing on Sponsored Products and Brands, specifically the Search Ranking and Interleaving (R&I) team. The role involves developing and applying GenAI and ML techniques to optimize ad ranking, allocation, and relevance on the search page. Key responsibilities include building real-time ML algorithms for ad auctions, developing multi-objective optimization methods, and researching new ML approaches to improve shopper experience and drive revenue. The role requires experience in building models for business applications and applying theoretical models in practice.

The role involves applying deep learning, neural networks, and transformer architectures to price prediction and forecasting problems within Amazon's Pricing Optimization group. It focuses on developing and deploying ML models at scale to improve pricing and promotion strategies, requiring collaboration with product, engineering, and science teams.

Manager for Navigation Science team at Amazon Prime Air, focusing on developing advanced navigation algorithms and flight software for delivery drones. Requires leadership experience, strong programming skills, and experience with agile development. The role involves defining system architectures, contributing to flight algorithms, and driving innovation in a safety-critical environment.

Product leader to define and build the vision for AI-driven communication experiences for Alexa, focusing on generative AI transforming Alexa into a proactive, personal communications partner. The role involves owning end-to-end communication experiences across household, global, and AI-powered productivity, and pioneering real-time, multimodal AI primitives.

The Economist II, Featured Merchant Algorithm role at Amazon focuses on developing and deploying machine learning models that determine the 'Buy Box' offer and surrounding customer experience on Amazon's platforms. This involves ranking and selecting the best offer based on factors like price, availability, and delivery, impacting billions of transactions daily. The role requires a PhD in economics, strong data-driven decision-making, collaboration with cross-functional teams, and expertise in prediction and forecasting with large datasets.

Sr. Manager of Applied Science with expertise in Statistical Machine Learning and/or Reinforcement Learning to drive research, development, and deployment of AI technology for supply chain optimization. The role involves managing a team of scientists, focusing on next-generation solutions for buying, placement, and fulfillment decisions, and translating customer needs into reusable software infrastructure. Key responsibilities include leading innovation in RL applications, building and developing a high-performing team, bridging technical possibilities with business requirements, and driving cross-functional collaboration.

This internship role focuses on applying data science and machine learning to solve complex problems in robotics at Amazon. Interns will design and implement solutions, research new algorithms, collaborate with experts, and build tools to improve robotics analytics and customer experience. The role involves working with various AI/ML fields including computer vision, LLMs, and deep learning within a robotics context.

Applied Scientist role focused on building machine learning models and technology to automatically monitor and classify billions of products in the Amazon catalog, ensuring compliance and safety. The role involves working with large datasets, deep learning for search matching and ranking, filtering, indexing, and document understanding, with a focus on delivering customer-facing experiences at Amazon scale.

Master's student internship focused on applying machine learning, NLP, computer vision, automated reasoning, or robotics to design and develop end-to-end systems for Amazon Science. The role involves working with large datasets, implementing systems, and potentially deploying solutions into production.

Senior Applied Scientist role focused on developing and launching end-to-end AI solutions, specifically recommendation systems leveraging generative models, for Amazon's Sponsored Products and Brands advertising platform. The role involves defining science vision, designing experiments, and collaborating with engineering and product teams to improve advertiser and shopper experiences.

Data Scientist III on the Shopbop/Zappos Catalog Tech team responsible for designing and implementing ML approaches to improve product catalog data quality, automate data capture and classification, and integrate ML models into production systems. The role involves working with computer vision and NLP, and influencing product decisions through data-driven insights.

Senior Machine Learning Engineer role focused on developing and launching AI solutions for Prime Video's recommendation and personalization systems, utilizing deep learning, GenAI, and reinforcement learning. The role involves end-to-end ownership, experimental design, and collaboration with cross-functional teams to impact millions of customers.

Manage a team of Applied Scientists, ML Engineers, and Software Development Engineers to develop science and engineering roadmaps for SPB ads CTR prediction using ML and Gen AI solutions. The role involves hiring, developing talent, and staying informed about scientific publications and industrial research trends. The team focuses on personalized shopping experiences through ML and GenAI solutions for response prediction and session-level understanding to optimize ad serving, targeting, sourcing, and bidding.

This role leads science and engineering for AI-powered sponsored product ads in offsite shopping experiences, focusing on generative AI and large-scale ML solutions. The goal is to revolutionize advertising by bridging human creativity with AI, impacting ad creation, optimization, performance analysis, and customer insights. The role involves extending campaigns to reach customers off-store and on third-party sites, working with external and internal partners, and driving results at scale with a GenAI-first approach. It requires significant experience in building large-scale ML/AI solutions and people management.

Principal Applied Scientist role focused on building next-generation personalized shopping experiences at Amazon using LLMs, transformer models, and large-scale ranking systems. The role involves innovating features and models, leading science innovation, driving the science roadmap, and mentoring scientists. It aims to create a personalized shopping experience tailored to customer intent and product catalog understanding.

Senior Machine Learning Engineer role at Amazon Prime Video focused on developing and launching AI solutions for recommendation and personalization systems. The role involves end-to-end ownership of ML models, including design, implementation, experimentation (A/B testing), and deployment for millions of customers. It requires experience with large-scale ML systems and recommendation systems.

This role focuses on developing and launching end-to-end AI solutions for Prime Video's search and discovery systems, utilizing deep learning, GenAI, and reinforcement learning. The scientist will design and conduct experiments, collaborate with engineers and product managers, and publish research findings. The role is within the consumer domain, aiming to improve customer experience for millions of users.

Applied Scientist II at Amazon Prime Video focusing on personalization and discovery science. The role involves developing ML models for recommendation and search systems using deep learning, online learning, and optimization methods. It requires staying updated with the latest modeling techniques, publishing research findings, and applying advanced approaches like foundation models to solve cold-start problems and discover niche customer interests. The scientist will work on highly scalable page personalization solutions and collaborate with engineers and product managers.

Senior Applied Scientist role at Amazon Advertising focused on building and deploying end-to-end machine learning models to improve traffic monetization and merchandise sales. The role involves leading ML efforts, performing hands-on analysis, driving ambiguous projects, and establishing scalable processes for model development and deployment.

Senior Applied Scientist role at Amazon Prime Video focusing on Playback Intelligence. The role involves applying machine learning and data science to optimize video streaming quality, detect anomalies, and leverage LLMs and generative AI. Responsibilities include end-to-end ownership of product and user experience, translating business requirements into ML deliverables, defining research directions, conducting experiments, and mentoring junior scientists. The role requires experience in building ML models for business applications and designing AI solutions for real-world use cases.

Principal Applied Scientist role focused on applying machine learning, optimization, and economics to improve Amazon's Stores business, specifically in areas like delivery speed, seller fees, and LLM applications. The role involves leading a team, developing scientific models, benchmarks, and services, and deploying solutions in partnership with product teams.