Careers

RBS (Retail Business Services) Tech team works towards enhancing the customer experience (CX) and their trust in product data by providing technologies to find and fix Amazon CX defects at scale. Our platforms help in improving the CX in all phases of customer journey, including selection, discoverability & fulfilment, buying experience and post-buying experience (product quality and customer returns). The team also develops GenAI platforms for automation of Amazon Stores Operations. As a Sciences team in RBS Tech, we focus on foundational ML research and develop scalable state-of-the-art ML solutions to solve the problems covering customer experience (CX) and Selling partner experience (SPX). We work to solve problems related to multi-modal understanding (text and images), task automation through multi-modal LLM Agents, supervised and unsupervised techniques, multi-task learning, multi-label classification, aspect and topic extraction for Customer Anecdote Mining, image and text similarity and retrieval using NLP and Computer Vision for product groupings and identifying duplicate listings in product search results. Key job responsibilities As an Applied Scientist, you will be responsible to design and deploy scalable GenAI, NLP and Computer Vision solutions that will impact the content visible to millions of customer and solve key customer experience issues. You will develop novel LLM, deep learning and statistical techniques for task automation, text processing, image processing, pattern recognition, and anomaly detection problems. You will define the research and experiments strategy with an iterative execution approach to develop AI/ML models and progressively improve the results over time. You will partner with business and engineering teams to identify and solve large and significantly complex problems that require scientific innovation. You will independently file for patents and/or publish research work where opportunities arise. The RBS org deals with problems that are directly related to the selling partners and end customers and the ML team drives resolution to organization level problems. Therefore, the Applied Scientist role will impact the large product strategy, identifies new business opportunities and provides strategic direction which is very exciting.

We are looking for a talented, organized, and customer-focused applied researchers to join our Pricing Optimization science group, with a charter to measure, refine, and launch customer-obsessed improvements to our algorithmic pricing and promotion models across all products listed on Amazon. This role requires an individual with exceptional machine learning modeling and architecture expertise, excellent cross-functional collaboration skills, business acumen, and an entrepreneurial spirit. We are looking for an experienced innovator, who is a self-starter, comfortable with ambiguity, demonstrates strong attention to detail, and has the ability to work in a fast-paced and ever-changing environment. Key job responsibilities * See the big picture. Understand and influence the long term vision for Amazon's science-based competitive, perception-preserving pricing techniques * Build strong collaborations. Partner with product, engineering, and science teams within Pricing & Promotions to deploy machine learning price estimation and error correction solutions at Amazon scale * Stay informed. Establish mechanisms to stay up to date on latest scientific advancements in machine learning, neural networks, natural language processing, probabilistic forecasting, and multi-objective optimization techniques. Identify opportunities to apply them to relevant Pricing & Promotions business problems * Keep innovating for our customers. Foster an environment that promotes rapid experimentation, continuous learning, and incremental value delivery. * Successfully execute & deliver. Apply your exceptional technical machine learning expertise to incrementally move the needle on some of our hardest pricing problems. A day in the life We are hiring a Sr. Applied Scientist to drive our pricing optimization initiatives. We drive cross-domain and cross-system improvements through: * shape and extend our RL optimization platform - a pricing centric tool that automates the optimization of various system parameters and price inputs. * Error detection and price quality guardrails at scale. * Identifying opportunities to optimally price across systems and contexts (marketplaces, request types, event periods) Price is a highly relevant input into Stores architectures; this role creates the opportunity to drive extremely large impact (measured in Bs not Ms), but demands careful thought and clear communication.

Join the next science and engineering revolution at Amazon's Delivery Foundation Model team, where you'll work alongside world-class scientists and engineers to pioneer the next frontier of logistics through advanced AI and foundation models. We are seeking an exceptional Applied Scientist to help develop innovative foundation models that enable delivery of billions of packages worldwide. In this role, you'll combine highly technical work with scientific leadership, ensuring the team delivers robust solutions for dynamic real-world environments. Your team will leverage Amazon's vast data and computational resources to tackle ambitious problems across a diverse set of Amazon delivery use cases. Key job responsibilities - Design and implement novel deep learning architectures combining a multitude of modalities, including image, video, and geospatial data. - Solve computational problems to train foundation models on vast amounts of Amazon data and infer at Amazon scale, taking advantage of latest developments in hardware and deep learning libraries. - As a foundation model developer, collaborate with multiple science and engineering teams to help build adaptations that power use cases across Amazon Last Mile deliveries, improving experience and safety of a delivery driver, an Amazon customer, and improving efficiency of Amazon delivery network. - Drive technical direction for specific research initiatives, ensuring robust performance in production environments. A day in the life As a member of the Delivery Foundation Model team, you’ll spend your day on the following: - Develop and implement novel foundation model architectures, working hands-on with data and our extensive training and evaluation infrastructure - Collaborate with fellow scientists in solving complex technical challenges, from trajectory planning to efficient multi-task learning - Collaborate with fellow engineers in building scalable and reusable infra to support model training, evaluation, and inference - Contribute to focused technical initiatives from conception through deployment, ensuring successful integration with production systems - Drive technical discussions within the team and and key stakeholders - Conduct experiments and prototype new ideas - Make significant hands-on contribution to technical solutions About the team The Delivery Foundation Model team combines ambitious research vision with real-world impact. Our foundation models provide generative reasoning capabilities required to meet the demands of Amazon's global Last Mile delivery network. We leverage Amazon's unparalleled computational infrastructure and extensive datasets to deploy state-of-the-art foundation models to improve the safety, quality, and efficiency of Amazon deliveries. Our work spans the full spectrum of foundation model development, from multimodal training using images, videos, and sensor data, to sophisticated modeling strategies that can handle diverse real-world scenarios. We build everything end to end, from data preparation to model training and evaluation to inference, along with all the tooling needed to understand and analyze model performance. Join us if you're excited about pushing the boundaries of what's possible in logistics, working with world-class scientists and engineers, and seeing your innovations deployed at unprecedented scale.

We're seeking an Applied Scientist to lead and innovate in applying advanced AI technologies that will reshape how businesses sell on Amazon. Our team is passionate about leveraging Machine Learning, GenAI, and Agentic AI to help B2B sellers optimize their operations and drive growth. Join Amazon Business 3P (Third Party - Sellers) - a rapidly growing global organization where we innovate at the intersection of AI technology and B2B commerce. We're reimagining how sellers reach and serve business customers, creating intelligent solutions that help them grow their B2B business on Amazon. From AI-powered Seller Central tools to smart business certifications, dynamic pricing capabilities, and advanced analytics, we're transforming how B2B selling happens. As an Applied Scientist II on our AB 3P Tech team, you'll drive the development and implementation of state-of-the-art algorithms and models for supervised fine-tuning and reinforcement learning. You'll work with highly technical, entrepreneurial teams to: - Design and implement AI models that power the B2B selling experience - Lead the development of GenAI products that can handle Amazon-scale use cases - Drive research and implementation of advanced algorithms for human feedback and complex reasoning - Make strategic AI technology decisions and mentor technical talent - Own critical AI systems spanning from Seller Central to Amazon Business detail pages Join us in shaping the future of B2B selling - we're building applied AI solutions that businesses love and trust for their day-to-day success. If you are scrappy and bias for action is your favorite Leadership Principle, you'll fit right in as we innovate across the seller experience to create significant impact in this fast-growing business. Key job responsibilities Key job responsibilities: - Collaborate with cross-functional teams of engineers, product managers, and scientists to identify and solve complex problems in Gen AI - Design and execute experiments to evaluate the performance of different algorithms and models, and iterate quickly to improve results - Think big about the arc of development of Gen AI over a multi-year horizon, and identify new opportunities to apply these technologies to solve real-world problems - Communicate results and insights to both technical and non-technical audiences About the team At Amazon Business Third Party (AB3P) Tech, we're revolutionizing B2B e-commerce by empowering sellers in the business marketplace. Our scope spans the complete B2B selling journey, from Seller Central to Amazon Business detail pages, cart, and checkout for merchant-fulfilled offers. Our entrepreneurial culture and global reach define us. We develop features across seller experience, delivery, certifications, fees, registration, and analytics, collaborating with worldwide teams and leveraging advanced AI technologies to continuously innovate. Working in true Day 1 spirit, we build next-generation solutions that shape the future of B2B commerce. Join us in building next-generation solutions that shape the future of B2B commerce.

Amazon Industrial Robotics Group is seeking exceptional talent to help develop the next generation of advanced robotics systems that will transform automation at Amazon's scale. We're building revolutionary robotic systems that combine cutting-edge AI, sophisticated control systems, and advanced mechanical design to create adaptable automation solutions capable of working safely alongside humans in dynamic environments. This is a unique opportunity to shape the future of robotics and automation at unprecedented scale, working with world-class teams pushing the boundaries of what's possible in robotic manipulation, locomotion, and human-robot interaction. This role presents an opportunity to shape the future of robotics through innovative applications of deep learning and large language models. At Amazon Industrial Robotics Group, we leverage advanced robotics, machine learning, and artificial intelligence to solve complex operational challenges at unprecedented scale. Our fleet of robots operates across hundreds of facilities worldwide, working in sophisticated coordination to fulfill our mission of customer excellence. We are pioneering the development of robotics foundation models that: - Enable unprecedented generalization across diverse tasks - Enable unprecedented robustness and reliability, industry-ready - Integrate multi-modal learning capabilities (visual, tactile, linguistic) - Accelerate skill acquisition through demonstration learning - Enhance robotic perception and environmental understanding - Streamline development processes through reusable capabilities The ideal candidate will contribute to research that bridges the gap between theoretical advancement and practical implementation in robotics. You will be part of a team that's revolutionizing how robots learn, adapt, and interact with their environment. Join us in building the next generation of intelligent robotics systems that will transform the future of automation and human-robot collaboration. Key job responsibilities As an Applied Science Manager in the Foundations Model team, you will: - Build and lead a team of scientists and developers responsible for foundation model development - Define the right ‘FM recipe’ to reach industry ready solutions - Define the right strategy to ensure fast and efficient development, combining state of the art methods, research and engineering. - Lead Model Development and Training: Designing and implementing the model architectures, training and fine tuning the foundation models using various datasets, and optimize the model performance through iterative experiments - Lead Data Management: Process and prepare training data, including data governance, provenance tracking, data quality checks and creating reusable data pipelines. - Lead Experimentation and Validation: Design and execute experiments to test model capabilities on the simulator and on the embodiment, validate performance across different scenarios, create a baseline and iteratively improve model performance. - Lead Code Development: Write clean, maintainable, well commented and documented code, contribute to training infrastructure, create tools for model evaluation and testing, and implement necessary APIs - Research: Stay current with latest developments in foundation models and robotics, assist in literature reviews and research documentation, prepare technical reports and presentations, and contribute to research discussions and brainstorming sessions. - Collaboration: Work closely with senior scientists, engineers, and leaders across multiple teams, participate in knowledge sharing, support integration efforts with robotics hardware teams, and help document best practices and methodologies.

As part of grocery replenishment organization, Sr. Applied Scientists own inventory optimization, distribution optimization, and end-to-end modeling / simulation of Amazon grocery supply chain utilizing optimization and machine learning toolsets. We are looking for a talented and experienced applied scientist with a passion for designing and implementing elegant scientific solutions for Amazon-scale problems. Key job responsibilities - Design and develop advanced mathematical optimization models and apply them to define strategic and tactical needs and drive the appropriate business and technical solutions in the areas of inventory optimization, distribution optimization, network design, and control theory. - Apply mathematical optimization and control techniques (linear, quadratic, SOCP, robust, stochastic, dynamic, mixed-integer programming, network flows, nonlinear, nonconvex programming, decomposition methods, model predictive control) and algorithms to design optimal or near optimal solution methodologies to be used by in-house decision support tools and software. - Research, prototype, simulate, and experiment with these models using modeling languages such as Java, Python, MATLAB, Mosel or R; participate in the production level deployment. - Closely work with software engineering teams and write production well-tested Java code for science modules within engineering-managed services. Provide time-sensitive on-call support and high-severity issue support when bugs are identified in production code. Improve code quality of legacy scientific production code. - Create, enhance, and maintain technical documentation and science designs. - Present to other Scientists, Product, and Software Engineering teams, as well as Stakeholders. - Lead project plans from a scientific perspective by managing product features, technical risks, milestones and launch plans. - Influence organization's long-term roadmap and resourcing, onboard new technologies onto Science team's toolbox, mentor other Scientists. A day in the life - Engage with customers to understand their problems. - Collaborate with product partners and peers to design and deliver algorithmic solutions to these problems. - Implement these solutions in java within engineering systems through close collaboration with engineering partners achieving high code quality. - Deploy and measure impact of implementations. - Support customers and stakeholders whenever deep-dives and enhancements are needed as they relate to scientific products the team owns. - Contribute to product roadmap through new innovations on behalf of customers. - Publish work in internal and external scientific community. About the team SCOT IB GRO Science team is comprised of applied scientists with strong optimization & ML science depth and object-oriented programming & design patterns knowledge. Given the scale of problems we solve for our customers and mission-critical nature of our solutions, systems thinking driven approach, with attention to algorithmic complexity, solution quality, simplicity, and extensibility are of critical importance. We collaborate with engineering teams closely and prioritize solving problems with minimally complex solutions while maintaining quality. We build solutions that must consistently improve customer experience with maximum transparency and explainability of decisions made by such solutions. We strive for every member of the team to be knowledgeable about every product that the team owns to enable meaningful collaboration within the team. We seek to publish our work at internal and external scientific communities when they produce novel solutions.

RBS (Retail Business Services) Tech team works towards enhancing the customer experience (CX) and their trust in product data by providing technologies to find and fix Amazon CX defects at scale. Our platforms help in improving the CX in all phases of customer journey, including selection, discoverability & fulfilment, buying experience and post-buying experience (product quality and customer returns). The team also develops GenAI platforms for automation of Amazon Stores Operations. As a Sciences team in RBS Tech, we focus on foundational ML research and develop scalable state-of-the-art ML solutions to solve the problems covering customer experience (CX) and Selling partner experience (SPX). We work to solve problems related to multi-modal understanding (text and images), task automation through multi-modal LLM Agents, supervised and unsupervised techniques, multi-task learning, multi-label classification, aspect and topic extraction for Customer Anecdote Mining, image and text similarity and retrieval using NLP and Computer Vision for product groupings and identifying duplicate listings in product search results. Key job responsibilities As an Applied Scientist, you will be responsible to design and deploy scalable GenAI, NLP and Computer Vision solutions that will impact the content visible to millions of customer and solve key customer experience issues. You will develop novel LLM, deep learning and statistical techniques for task automation, text processing, image processing, pattern recognition, and anomaly detection problems. You will define the research and experiments strategy with an iterative execution approach to develop AI/ML models and progressively improve the results over time. You will partner with business and engineering teams to identify and solve large and significantly complex problems that require scientific innovation. You will help the team leverage your expertise, by coaching and mentoring. You will contribute to the professional development of colleagues, improving their technical knowledge and the engineering practices. You will independently as well as guide team to file for patents and/or publish research work where opportunities arise. The RBS org deals with problems that are directly related to the selling partners and end customers and the ML team drives resolution to organization level problems. Therefore, the Applied Scientist role will impact the large product strategy, identifies new business opportunities and provides strategic direction which is very exciting.

AWS Deep Science for Systems & Services is looking for a Sr. Manager, Applied Science who will lead a team of world class scientists to work on foundation models, large-scale representation learning, and distributed learning methods and systems. At AWS Deep Science for Systems & ServicesL you lead a team inventing, implementing, and deploying state of the art machine learning algorithms and systems. You will build prototypes and innovate on new representation learning solutions, interact closely with our customers and with the academic and research communities. You will be at the heart of a growing and exciting focus area for AWS and work with other acclaimed engineers and world famous scientists. Large-scale foundation models have been the powerhouse in many of the recent advancements in computer vision, natural language processing, automatic speech recognition, recommendation systems, and time series modeling. Developing such models requires not only skillful modeling in individual modalities, but also understanding of how to synergistically combine them, and how to scale the modeling methods to learn with huge models and on large datasets. Join us to work as an integral part of a team that has diverse experiences in this space. We actively work on these areas: - Hardware-informed efficient model architecture, training objective and curriculum design - Distributed training, accelerated optimization methods - Continual learning, multi-task/meta learning - Reasoning, interactive learning, reinforcement learning - Robustness, privacy, model watermarking - Model compression, distillation, pruning, sparsification, quantization

We are looking for a Data Scientist to join our Prime Video team in Israel, focusing on personalizing customer experiences through Search and Recommendations. Our team leverages Machine Learning (ML) to deliver tailored content discovery, helping millions of customers find the entertainment they love. You will work on large-scale experimentation, measurement frameworks, and data-driven decision-making that directly shapes how customers interact with Prime Video. Key job responsibilities - Design metrics frameworks and evaluation systems to measure the quality, performance, and reliability of algorithmic solutions - Lead the design, execution, and analysis of A/B tests to validate product hypotheses and quantify customer impact - Communicate analytical findings and recommendations clearly to both technical teams and business stakeholders, driving data-informed decisions - Partner with Applied Scientists, Software Engineers, and Product Managers to define requirements, evaluate models, and drive data-informed product decisions - Act as the subject matter expert for data structures, metrics definitions, and analytical best practices - Identify opportunities for improving customer experience through deep-dive analyses of user behavior and algorithm performance

Are you a scientist interested in pushing the state of the art in Information Retrieval, Large Language Models and Recommendation Systems? Are you interested in innovating on behalf of millions of customers, helping them accomplish their every day goals? Do you wish you had access to large datasets and tremendous computational resources? Do you want to join a team of capable scientist and engineers, building the future of e-commerce? Answer yes to any of these questions, and you will be a great fit for our team at Amazon. Our team is part of Amazon’s Personalization organization, a high-performing group that leverages Amazon’s expertise in machine learning, generative AI, large-scale data systems, and user experience design to deliver the best shopping experiences for our customers. Our team is building next-generation personalization systems powered by Large Language Models. We are tackling novel research challenges to help customers discover products they'll love - at Amazon scale and latency requirements. We are a team uniquely placed within Amazon, to have a direct window of opportunity to influence how customers will think about their shopping journey in the future. As an Applied Science Manager, you will lead a team of scientists working at the frontier of LLM-based personalization. You will set the technical vision, drive the research agenda, and ensure your team delivers production-ready solutions. You will hire, mentor, and develop world-class scientists while fostering a culture of innovation and scientific rigor. You will partner closely with engineering and product teams to translate ambitious research into customer-facing impact, and represent your team's work to senior leadership. Please visit https://www.amazon.science for more information.