Amazon

Applied Scientist II at Amazon Prime Video focused on developing ML models for recommendation and search systems using deep learning, online learning, and optimization methods. The role involves end-to-end ownership of product and user experience, working with advanced approaches like foundation models to tackle cold-start problems and discover niche interests. The scientist will also publish research findings and collaborate with engineering and product teams.

Senior Applied Scientist role focused on developing and productionizing AI/ML models for ad measurement and performance analysis within Amazon Ads. The role involves end-to-end solution development, leveraging Generative AI, classical ML, NLP, and Computer Vision to provide insights and automate workflows for advertisers. Responsibilities include model development, experimentation, collaboration with engineering and business teams, and mentoring junior scientists.

Applied Scientist role at Amazon Ads focusing on measurement science, developing solutions for performance measurement products, sales impact analysis, and AI tools for customer insights and workflow automation. The role involves end-to-end ownership of measurement solutions, from design to production, leveraging Generative AI, classical ML, Causal Inference, NLP, and Computer Vision.

The Sponsored Products and Brands team at Amazon Ads is seeking an Applied Scientist to leverage generative AI and machine learning to revolutionize advertising experiences. This role involves driving end-to-end ML projects, analyzing large datasets, building and deploying models into production, and establishing scalable processes for ML development and serving. The focus is on creating innovative ad tech and shopping experiences off the store, working with external and internal partners to connect systems, understand customers, and drive results at scale, with a GenAI-first approach.

Senior Applied Scientist role focused on developing and launching AI solutions for Amazon's Sponsored Products and Brands advertising business. This involves building recommendation systems leveraging generative models, designing and implementing end-to-end AI solutions, and defining a long-term science vision. The role requires experience in building ML models, deep learning, and working with large-scale distributed systems.

Manager for an AWS Applied AI Solutions team focused on building foundational systems and consumer-facing features for trustworthy AI experiences at scale within the supply chain domain. The role involves leading engineering teams, driving technical strategy for privacy-preserving and responsible AI, and developing enterprise-grade AI applications.

The Applied Scientist will build next-generation conversational shopping experiences for Amazon Rufus, developing data-driven solutions and deploying models into production. This role involves collaboration with cross-functional teams and leveraging Amazon's data and AWS resources.

Applied Scientist role at Amazon Prime Video focusing on leveraging NLP and Computer Vision research to enhance video content understanding and customer experience. The role involves leading research direction, creating roadmaps, and developing models for business applications, with an emphasis on delivering state-of-the-art digital video experiences.

Research scientist role focused on developing and launching new AI technologies for personalization in e-commerce, leveraging LLMs, recommendation systems, and information retrieval.

Principal Product Manager, Technical for Alexa Connections, focusing on building AI-native communication experiences using generative AI, LLMs, real-time communications, voice, and GUIs. The role involves strategizing, driving product roadmaps, and launching 0-1 product lines, working cross-functionally with engineering, science, and design teams to deliver delightful customer experiences.

Manager of Data Science at AWS responsible for overseeing a team that builds large-scale distributed systems for abuse detection. The role involves defining business goals, aggregating data, managing research vision, mentoring scientists, and ensuring successful integration of AI models into production. Requires experience in managing data science teams, cross-functional projects, ML techniques, generative AI, foundation models, MLOps, and production deployment of AI systems.

Principal Product Manager Tech for Prime Video Personalization & Discovery, focusing on owning the vision, strategy, and roadmap for core recommendation systems and ML models. The role involves translating business problems into model requirements, defining metrics, leading A/B testing, and making trade-off decisions for ML-powered features at scale, with a strong emphasis on customer value and business outcomes.

Applied Scientist II role at Amazon Ads focused on building production ML and bandit solutions to customize the Sponsored Products search experience. The role involves determining ad placement, quantity, and targeting using machine learning, causal inference, and optimization techniques. It emphasizes improving shopper discovery and advertiser reach by modeling shopper responses and optimizing ad allocation and ranking on the search page, with a recent focus on integrating LLMs/GenAI for production use cases.

Software Development Engineer role at Amazon Alexa Connections, focusing on integrating generative AI and machine learning into communication features to enhance customer experiences. The role involves designing and building scalable, fault-tolerant systems for AI/ML workloads, including Gen AI inference and training pipelines, within an agile environment.

Manager for an Applied Scientist team focused on optimizing the returns and re-commerce process using ML, NLP, and Information Retrieval. The role involves managing scientists and engineers, developing ML models for business applications, and building scalable software systems.

Senior Applied Scientist role focused on developing AI-powered Discovery systems for AWS Marketplace, specializing in personalization, search, and recommendation systems. The role involves leading research, design, and development, translating scientific techniques into scalable solutions, and mentoring other scientists. It aims to accelerate cloud migrations and support partner growth.

This role focuses on delivering secure Generative AI solutions to enterprise customers, acting as both a security leader and hands-on practitioner. It involves conducting security assessments, architecting and implementing security controls for GenAI applications, and building reusable security patterns and accelerators. The role also involves developing innovative GenAI-powered security solutions and contributing to thought leadership.

Applied Scientist role at Amazon Prime Video focused on building machine learning systems for content presentation and discovery. The role involves working with multi-modal embeddings, contextualized ranking, reinforcement learning, and recommender systems to improve customer engagement with the Prime Video catalog.

Applied Scientist role focused on building and deploying end-to-end machine learning solutions to prevent eCommerce fraud and manage transaction safety within Amazon's production environment. The role involves innovating with GenAI/LLM/VLM technologies, analyzing large datasets, and creating automated risk evaluation and operational systems.

Applied Scientist role at Amazon Business Ads focusing on building and deploying scientifically novel software solutions for B2B advertising products. Requires experience in model building for business applications and proficiency in Python/deep learning frameworks.

Applied Scientist role focused on designing, developing, and deploying ML and computer vision models for Amazon's in-store grocery technologies, including smart carts, inventory intelligence, personalization, and store operations. The role involves end-to-end model development from ideation to production, with a focus on solving real-world problems at scale within the grocery domain.

This role is for a Senior Applied Science Manager on the Stores Economics and Science team at Amazon. The team uses economics, statistics, and machine learning to understand and design Amazon's buyer and seller economy. The manager will provide structure for complex business problems, work with ML scientists to validate models, and help partners translate analysis into impactful actions. The role requires experience in building large-scale ML/AI solutions, leading scientists, and developing junior talent.

Machine Learning Engineer focused on developing and deploying ML products for network management within Amazon Infrastructure Engineering, aiming to improve customer experience and revolutionize business operations.

Senior Applied Scientist role focused on leveraging generative AI and machine learning to re-imagine advertising experiences for Amazon Ads' Sponsored Products and Brands. The role involves leading ML efforts, analyzing large datasets, building and deploying ML models for insights, traffic monetization, and personalized shopping experiences, and driving end-to-end ML projects. It also includes running A/B experiments, establishing scalable processes, researching new ML approaches, and recruiting/mentoring other scientists.

Applied Scientist II role at Amazon Ads focused on building production ML and bandit solutions to customize the Sponsored Products search experience. The role involves determining ad placement, quantity, and targeting using machine learning, causal inference, and optimization techniques. It emphasizes improving shopper discovery and advertiser reach by modeling shopper responses and optimizing ad allocation and ranking on the search page, with a recent focus on integrating LLMs/GenAI for production use cases.

Applied Scientist role focused on developing and launching AI solutions for Prime Video's search and personalization systems, involving deep learning, GenAI, and reinforcement learning. The role requires end-to-end ownership from design to launch, including experimentation and evaluation, with a strong emphasis on delivering customer-facing products. Research publication is also a component.

The Applied Scientist will lead Machine Learning efforts for Amazon Ads' Demand Forecasting & Guidance team. This role involves hands-on analysis and modeling of large datasets to develop insights, build and deploy ML models into production, and run A/B experiments. The goal is to create best-in-class forecasting products for advertisers to predict campaign outcomes and optimize ad performance, directly impacting key business decisions.

Applied Scientist II at Amazon focused on improving shopping experiences using LLMs. Requires 3+ years of building models for business applications, a PhD or Master's with 4+ years of experience, and a publication/patent record. Experience with algorithms, data structures, optimization, data mining, and parallel computing is expected.

Applied Scientist role focused on developing and launching AI solutions for Prime Video's personalization and discovery systems, involving deep learning, GenAI, RL, and optimization. The role requires end-to-end ownership, experimental design (offline and A/B testing), and publishing research findings. Experience with recommender systems and personalization is preferred.

Applied Scientist role focused on building and delivering state-of-the-art science and engineering solutions for Amazon's Stores business, leveraging machine learning, optimization, and economics to improve business metrics. The role involves developing and maintaining scientific models, benchmarks, and services, and deploying solutions in partnership with product teams.

Principal Product Manager for Prime Video's Personalization and Monetization, focusing on ML-powered features, recommendation systems, and customer experience. This role involves defining product strategy, translating business problems into algorithmic requirements, and guiding the ML lifecycle to ship scalable, customer-centric AI features.

Applied Scientist role focused on developing and launching customer-obsessed pricing algorithms for billions of products worldwide. This involves leveraging large-scale multi-modal datasets, applying machine learning, predictive modeling, causal inference, and reinforcement learning to optimize pricing strategies and tools for sellers. The role emphasizes collaboration with product and engineering teams, continuous learning, and delivering business impact through innovative pricing solutions.

Applied Scientist role focused on developing and productizing AI solutions for enterprise services within AWS. The role involves designing and implementing ML systems for diverse applications, creating scalable algorithms, conducting experimentation with advanced techniques (LLMs, CV, agentic AI), and collaborating with engineering and product teams to deliver customer impact. The primary output is shipped AI products, with a secondary focus on agentic AI systems.

The Applied Scientist II role on the Amazon Search team focuses on inventing signals and algorithms for machine-learned ranking models to improve search quality for millions of customers. The role spans the entire development pipeline, from data analysis and prototyping to A/B testing and production deployment.

Data Scientist II at Audible (Amazon) focused on building production-ready LLM solutions and recommendation systems. Requires a Master's degree and 2+ years of experience in data science, ML modeling, Python/R, and non-linear models. Experience with LLMs (programmatic access, evaluation, fine-tuning), recommendation systems, and SQL/ETL is required.

Applied Scientist II at Amazon Fulfillment Technology (AFT) Science, focusing on developing production solutions for Amazon's Fulfillment Network using operations research, optimization, statistics, machine learning, and GenAI/LLM. The role involves designing, building, and deploying scalable mathematical models and optimization-driven solutions to improve process efficiency and associate experience within the fulfillment network. Collaboration with scientists, software engineers, and product managers is key, with a focus on translating research into production systems.

Senior Manager role focused on leading AI/ML innovation for network planning solutions, involving demand forecasting and network optimization algorithms. The role requires developing and deploying production-ready models, architecting scalable AI/ML infrastructure, and driving scientific innovation from research to production, ultimately translating AI/ML capabilities into measurable business outcomes. It emphasizes leading a team of applied scientists and collaborating with cross-functional partners.

Senior Applied Scientist role focused on using ML/AI to understand demand-side signals in e-commerce, empower sellers to grow their business, and improve customer experience. Responsibilities include developing scalable seller-facing solutions, analyzing business data, designing and evaluating innovative models, and collaborating with engineering teams for real-time implementation.

Applied Scientist role at Amazon Ads focusing on Generative AI, AI Agents, and large-scale ML for demand forecasting. Responsibilities include leading ML initiatives, developing and optimizing forecasting models, building and deploying ML models, designing A/B experiments, establishing scalable ML infrastructure, and researching innovative ML techniques. Requires 3+ years of model building experience, a PhD or Master's with 4+ years of experience in a related field, and programming experience in Java, C++, or Python. Preferred qualifications include experience with experimental design and deep learning frameworks.

The role focuses on applying advanced analytical, statistical, and machine learning techniques to improve Amazon's Selling Partner experience through a Generative AI-powered conversational assistant. Responsibilities include analyzing seller pain points, evaluating feature performance, designing measurement frameworks (A/B testing, causal inference), applying NLP and statistical modeling to unstructured data, and partnering with cross-functional teams to influence product roadmaps. The goal is to enhance the Selling Assistant by responding to seller feedback and implementing fixes in the GenAI solution.

The Sr. Applied Scientist Pricing Optimization role at Amazon Leo focuses on building foundational ML models to optimize pricing and product feature strategies for a satellite broadband network. This involves predicting customer behavior, modeling multi-product bundling, and implementing scalable inference systems.

Product Manager leader for a Generative AI team within Amazon Ads, focusing on building AI-driven solutions for ad creatives (images, videos, text). The role involves owning vision and strategy, partnering with science and engineering teams, and launching zero-to-one products with large-scale impact.

Applied Scientist role focused on developing and deploying machine learning models to optimize marketing initiatives and predict customer behavior for Amazon's consumer business. Requires strong quantitative modeling, statistical methods, and experience with deep learning.

Senior Applied Scientist role focused on developing next-generation advanced robotics systems that combine AI, control systems, and mechanical design for automation at Amazon's scale. The role involves research and implementation of deep learning and LLMs for robotics, with a focus on simulation, physics-based modeling, and sim-to-real gap reduction.

Applied Scientist role focused on developing and implementing forecasting and optimization models using ML and GenAI to support real estate and store planning decisions for Amazon's grocery business. The role involves analyzing large datasets, building end-to-end solutions, and collaborating with cross-functional teams to drive adoption of insights and models.

Research Scientist II Intern/Co-op role in Amazon's Personal Robotics Group, focusing on developing intelligent robotic products and systems. The role involves research in areas like robotics manipulation, autonomous navigation, locomotion, controls, perception, robot learning, AI, ML, computer vision, LLMs, and HRI, with a goal of impacting millions of customers. The position is for PhD students and involves working on scalable research projects.

Data Scientist for Prime Air focusing on applied ML and experimentation to improve customer journey, drive expansion, and optimize delivery operations. The role involves developing statistical and ML techniques, building predictive models, designing experiments, and presenting findings to leadership, with a focus on shipping models that have a direct business impact.

Senior Manager, Applied Science for Marketing Measurement and Performance Science (MAPS) at Amazon. This role focuses on building scalable ML and causal inference solutions to estimate marketing effectiveness and provide insights for marketing teams. It involves leading a team of scientists, developing end-to-end causal inference models, and influencing multi-billion dollar investment decisions. The role requires expertise in ML/DL, statistics, economics, and handling large datasets at scale, with a focus on delivering data-driven solutions that impact business strategy and customer behavior.