Amazon

The Applied Scientist will work on building industry-leading Conversational AI Systems, focusing on Natural Language Understanding, Dialog Systems, Generative AI with LLMs, and Applied Machine Learning. The role involves developing novel algorithms and modeling techniques to advance human language technology, impacting millions of customers through products and services. The scientist will gain hands-on experience with Amazon's text, structured data, and large-scale computing resources.

Senior Applied Scientist at AWS Healthcare AI focused on developing and researching AI-driven clinical solutions to transform patient-clinician interaction and care documentation. The role involves leading research, developing new ML techniques, and ensuring research translates into impactful products, with a focus on generative AI experiences.

This role focuses on applying AI and machine learning to optimize Amazon's last-mile delivery network. Responsibilities include developing sophisticated ML models for logistics, forecasting, and resource allocation, architecting AI-powered systems, implementing deep learning for image recognition, and developing reinforcement learning for adaptive scheduling. The role also involves designing AI agents for autonomous decision-making and creating models for customer behavior analysis. A strong emphasis is placed on research, publishing findings, and leveraging big data and cloud platforms.

Applied Scientist II role focused on developing foundation models for industrial robotics, integrating multi-modal learning, skill acquisition, perception, and environmental understanding. The role involves leveraging, adapting, and optimizing state-of-the-art models, conducting rigorous experimentation, building evaluation benchmarks, and contributing to data and training workflows. It requires strong programming skills in Python and experience in deep learning areas like computer vision, multimodal models, or RL for robotics.

PhD intern/co-op role in Amazon's Personal Robotics Group focusing on research and development of intelligent robotic products, including Amazon Astro. The role involves working on the full spectrum of robotics, from hardware design to software and control systems, with a focus on manipulation, locomotion, and human-robot interaction. Requires a PhD in a relevant field and experience in programming languages like Python, C++, or Java.

Applied Scientist role focused on developing AI/ML solutions for Last Mile Delivery Automation, combining expertise in machine learning, computer vision, and robotics for perception, navigation, and path planning. The role involves transforming research into production-ready solutions and collaborating with engineering teams.

This role focuses on designing and deploying GenAI, NLP, and Computer Vision solutions for Amazon's retail business services, aiming to enhance customer experience and operational efficiency. The scientist will develop novel ML techniques for task automation, text and image processing, and anomaly detection, with a strong emphasis on LLM Agents and multi-modal understanding.

The Amazon Smart Vehicles (ASV) science team is seeking an Applied Scientist with expertise in advanced LLM technologies to create personalized services for drivers and passengers, enhancing their experience on the road. The role involves innovating in AI research, developing novel algorithms, and applying theoretical models in an applied environment, with direct application to Amazon products. The scientist will leverage Amazon's data and computing resources to advance generative AI and work closely with other teams to drive impact.

This role focuses on developing next-generation advanced robotics systems by combining AI, control systems, and mechanical design for automation at Amazon's scale. The intern will contribute to research bridging theoretical advancements and practical implementation in robotics, focusing on areas like dexterous manipulation, locomotion, and human-robot interaction, leveraging deep learning and LLMs.

The AWS Neuron Science Team is seeking scientists to enhance their software stack for ML accelerators (Trainium and Inferentia). The role involves working with customers to identify adoption barriers, collaborating with engineering teams on solutions, and advancing ML systems. Key areas include AI for Systems (kernel/code generation), ML Compiler techniques, System Robustness, and Efficient Kernel Development.

Senior Applied Scientist role focused on advancing LLM code intelligence through reinforcement learning and post-training methodologies, with a strong emphasis on research, publication, and deploying these models into production systems for developers.

Research Scientist role focused on developing and optimizing Generative AI models for edge devices, involving model compression techniques, custom ML hardware, and theoretical understanding of deep learning and information theory. The role involves co-authoring research papers and collaborating with cross-functional teams.

This role is for a PhD student intern/co-op focused on robotics research, specifically in areas like manipulation, perception, motion planning, and autonomous mobile robots. The role involves applying machine learning, computer vision, and potentially LLMs to solve real-world robotics problems, with a focus on developing research prototypes and seeing them through from concept to working prototype. The work touches on data collection/preparation for training and research.

This role focuses on building next-generation models for intelligent automation within AWS Agentic AI. The scientist will develop innovative solutions for complex problems, focusing on areas like autonomous agents, API orchestration, planning, large multimodal models (especially vision-language), reinforcement learning, and sequential decision making. The role involves partnering with technology and business teams, utilizing extensive data and computational resources, and collaborating with engineers. There's an expectation to publish findings at peer-reviewed conferences.

Lead a team of scientists to research and prototype Machine Learning applications, focusing on Agentic AI and LLM solutions for seller experience, trust, and safety. The role involves designing and implementing large-scale, end-to-end business solutions and influencing technical strategy.

The Principal Applied Scientist role at Amazon's Alexa International team focuses on defining research directions, inventing and applying ML techniques, conducting experiments, publishing results, and translating research into practice for expanding Alexa's reach across countries, languages, devices, and cultures. The role requires a PhD in AI/ML/NLP with 10+ years of experience, a strong publication record, and expertise in building and deploying ML solutions at scale.

This role focuses on analyzing and evaluating conversational interaction data to support the training and evaluation of LLMs and machine learning models for Alexa's speech interfaces. The Language Data Scientist will own data analysis, research requests, and contribute to developing annotation workflows and evaluation conventions.

Applied Scientist role focused on the intersection of AI and program analysis for a deep learning compiler stack, optimizing models for ML accelerators like Trainium. Responsibilities include designing, developing, and deploying analyzers, architecting tooling, and publishing research in compiler technology and deep learning systems software.

Research Scientist role focused on applying Operations Research, forecasting, machine learning, and decision optimization to solve large-scale problems in Amazon's Global Real Estate and Facilities (GREF) organization. The role involves translating business problems into mathematical solutions, building scalable algorithms, and influencing operational decisions to optimize areas like employee routes, demand forecasting, capacity planning, resource allocation, cost reduction, and service reliability.

Research Scientist role focused on applying Operations Research, forecasting, machine learning, and decision optimization to solve large-scale problems in Amazon's Global Real Estate and Facilities (GREF) organization. The role involves translating business problems into mathematical solutions, building scalable algorithms, and influencing operational decisions to optimize areas like employee routes, demand forecasting, capacity planning, resource allocation, cost reduction, and service reliability.

This role focuses on applying advanced automated reasoning techniques, including SAT, SMT, symbolic simulation, and program analysis, to solve complex problems within AWS. The goal is to enhance privacy and sovereignty for AWS services, impacting business and customer outcomes through scientific innovation and strategic problem-solving.

Applied Scientist role focused on automated reasoning, privacy, and sovereignty within AWS. Requires a Ph.D. and experience in areas like SAT, SMT, symbolic simulation, and program analysis. The role involves solving complex problems, designing and implementing solutions, and providing technical influence across organizations.

Applied Scientist role focused on automated reasoning, privacy, and sovereignty within AWS. The role involves solving complex problems, designing and implementing solutions, and providing cross-organizational technical influence. Requires a PhD or Master's with significant applied research experience in areas like SAT, SMT, theorem proving, symbolic simulation, program analysis, or type systems. Experience with specific programming languages like O'Caml, Dafny, Haskell, Lean, or Rust is preferred.

The Applied Scientist role in AWS Automated Reasoning focuses on developing advanced solutions for automated reasoning, privacy, and sovereignty within AWS. This involves solving complex problems, designing and implementing solutions with long-term impact, and providing cross-organizational technical influence. The role requires deep knowledge in areas like SAT, SMT, mechanical theorem proving, symbolic simulation, and program analysis, with a Ph.D. and 4+ years of applied research experience.

Applied Scientist role focused on automated reasoning, privacy, and sovereignty within AWS. Requires a PhD and experience in areas like SAT, SMT, theorem proving, or program analysis. The role involves solving complex problems, designing and implementing solutions, and providing cross-organizational technical influence.

Applied Scientist role at Amazon Ads focusing on generative AI for sponsored products and brands. The role involves developing and researching real-time ML algorithms for ad auctions and multi-objective optimization, aiming to improve customer experience and drive revenue. It requires end-to-end ML project ownership in a highly ambiguous and large-scale environment.

Economist II role focused on causal inference and machine learning for Prime Video Ads, involving experiment design, model building, and translating findings into business decisions. Requires a quantitative approach and end-to-end model implementation.

This role focuses on improving existing machine learning methodologies within Amazon's supply chain optimization technologies. Responsibilities include analyzing large datasets, developing new data sources, enhancing and testing models, running computational experiments, and fine-tuning model parameters. The role also involves formalizing model assumptions, identifying outliers, and communicating findings to various stakeholders. Collaboration with internal and external researchers, including publishing papers, is expected.

Applied Scientist role at Amazon Prime Video focusing on personalization and discovery science. The role involves developing AI solutions for search systems using deep learning, GenAI, and reinforcement learning, with end-to-end ownership from design to launch. It requires designing and conducting experiments, and publishing research findings. The team owns science solutions for search experience, including sourcing, relevance, and ranking.

This role focuses on developing and applying advanced econometric and machine learning models for Amazon's advertising products. The primary responsibilities include designing and analyzing large-scale experiments, developing novel causal inference methodologies for attribution and incrementality measurement, inventing optimization frameworks for bidding and targeting strategies, and defining the science roadmap for ads measurement and optimization. The role also involves building structural and reduced-form models to quantify advertising impact on consumer behavior and partnering with engineering teams to operationalize these models into production systems. The position requires a PhD in a quantitative field, extensive industry experience, and proficiency in big data and machine learning.

Senior Computational Biologist role focused on developing advanced computational methods and predictive models for complex, multi-modal datasets in the healthcare space. The role involves building interpretable models, integrating diverse data sources, and uncovering actionable insights, operating within an entrepreneurial and rapidly evolving environment.

This role focuses on building and refining Machine Learning and Generative AI models for the Ad Sales business, aiming to optimize workflows, provide insights, and drive efficiency for account teams. It involves conceptualizing research, guiding technical approaches, conducting data analysis, running A/B experiments, and working with engineers to deliver end-to-end solutions into production.

This role is for a PhD student intern focused on research science at Amazon. The intern will apply advanced statistical techniques and AI/ML technologies to solve complex problems, implement prototypes, and work with large datasets. Responsibilities include data collection, analysis, interpretation, developing and testing hypotheses, documenting findings, and collaborating with team members. The role emphasizes hands-on scientific work, data analysis, experimental design, and computational modeling.

This role focuses on developing advanced robotics systems that integrate AI, control systems, and mechanical design for automation. The scientist will design and implement whole-body control methods for balance, locomotion, and dexterous manipulation, utilizing state-of-the-art learned and model-based control methods, including imitation learning and reinforcement learning. The goal is to create robust, safe, real-time controllers for robots operating in dynamic environments and alongside humans.

Economist role focused on leading research, econometric modeling, and analysis to understand customer preferences and inform business operations. This involves developing analytic tools and economic models, including generative AI agents, to determine customer promise by considering inventory, fulfillment, carrier capabilities, customer preferences, and economic impacts. The role requires designing, building, and validating GenAI agents against traditional econometric models and production experiments, with the goal of driving changes in transportation and fulfillment networks.

PhD student internship focused on Automated Reasoning for cloud computing, involving research into novel approaches, development of solutions, and deployment into production. Expertise sought in theorem proving, SAT/SMT solvers, program analysis, and synthesis, with a potential link to ML/LLMs.

Seeking a Senior Research Scientist to lead the design and implementation of autonomous experimental research platforms leveraging data science and AI for sustainable materials innovation. This role combines Physical AI with materials chemistry to accelerate discovery and validation, establishing scientific strategy and technical roadmaps for next-generation autonomous capabilities.

Senior Research Scientist role focused on building and validating AI models to quantify the impact of Amazon's operational presence on local communities. The role involves designing causal frameworks, predictive models, and automated causal discovery systems using LLMs and document understanding. It also includes deploying production ML forecasting systems with multi-modal data sources and mentoring junior scientists. The work is at the intersection of computational social science, AI, and operational planning, influencing decisions affecting thousands of communities daily.

This role focuses on building next-generation software verification tools by combining AI, cloud computing, and formal methods. The scientist will explore generative AI techniques for formalizing requirements, generating tests, and repairing proofs, and will work on agentic systems to ensure AI agents operate within safety boundaries.

This role focuses on applying and researching novel machine learning approaches, particularly deep learning methods for multi-objective optimization, to develop real-time algorithms for allocating billions of ads daily in advertising auctions. The work involves end-to-end ML projects with ambiguity and scale, aiming to improve customer experience and drive revenue. The role also involves recruiting and mentoring scientists.

Applied Scientist role at Amazon Ads focusing on generative AI for sponsored products, developing real-time ML algorithms for ad allocation and multi-objective optimization. The role involves end-to-end ML projects with ambiguity and scale, aiming to improve customer experience and drive revenue. It also includes researching new ML approaches and potentially recruiting/mentoring scientists.

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.

MS or PhD student internship in machine learning, deep learning, generative AI, LLMs, speech technology, robotics, computer vision, optimization, operations research, quantum computing, automated reasoning, or formal methods. Focus on inventing, designing, and implementing state-of-the-art solutions. Will own design and development of end-to-end systems, write technical white papers, create roadmaps, and drive production-level projects. Opportunity to design new algorithms and models, and deploy them into production.

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.

Applied Scientist role at Amazon Prime Video focusing on content localization, understanding, and enrichment using NLP and computer vision. The role involves leading research direction, developing deep learning algorithms, and potentially building agentic systems for content understanding.

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

Applied Scientist III role at Amazon Web Services focusing on the design, development, evaluation, and deployment of data-driven models and analytical solutions for ML and NL applications. Responsibilities include applying statistical modeling, optimization, and ML techniques, building and deploying models in production, and researching novel ML approaches. Requires a Master's degree in a related field and experience in programming and developing supervised/unsupervised ML models.

Internship role for MS or PhD students in Speech, Robotics, Computer Vision, or Machine Learning/Deep Learning. Focuses on building large-scale ML systems using large datasets and translating business requirements into prototypes. Involves analyzing and modeling terabytes of text, images, and other data.