Careers

** Join Our Innovative Computer Vision Team at Amazon, Australia ** Are you passionate about developing generative models to transform the next generation of e-commerce platform and build AI models used by millions of customers? We invite you to be part of our high-performing Computer Vision team at Amazon located in Melbourne, Australia. As a member of our international Machine Learning group, you will work closely with other senior scientists in developing generative AI solutions that leverage vast amounts of Amazon data and advanced cloud computing resources. Our mission is to create next-generation media content that delivers an unforgettable shopping experience for our customers in emerging marketplaces. We are seeking talented Computer Vision Scientists with a Masters in Computer Science or in a related field. This is an opportunity for you to build innovative AI techniques that tackle real-world business challenges. Join a team dedicated to advancing AI technology at Amazon and transforming it into impactful business solutions. #austechjobs Key job responsibilities - Build, train and evaluate generative AI models tailored to our business use cases - Communicate clearly within the team to understand and align on scope and requirements - Implement novel machine learning techniques to solve customer problems - Publish papers at Tier-1 CV/ML conferences

We are seeking a highly skilled Data Scientist to join our Machine Learning Architecture team, focusing on power and performance optimization for ML acceleration workloads across Amazon's global data center infrastructure. This role combines advanced data science techniques with deep technical understanding of ML hardware acceleration to drive efficiency improvements in training and inference workloads at massive scale. Key job responsibilities ata Analysis & Optimization * Analyze power consumption and performance metrics across all Amazon data centers for machine learning acceleration workloads * Develop predictive models and statistical frameworks to identify optimization opportunities and performance bottlenecks * Create automated monitoring and alerting systems for power and performance anomalies Strategic Planning & Deployment Guidance * Provide data-driven recommendations for server deployments and capacity planning decisions across Amazon's global data center network * Develop optimization scenarios and business cases to improve capacity delivery efficiency to customers worldwide * Support strategic decision-making through comprehensive analysis of power, performance, and cost trade-offs Cross-Functional Collaboration * Partner with software engineering teams to optimize ML frameworks, drivers, and runtime systems * Collaborate with hardware engineering teams to influence chip design, server architecture, and cooling system optimization * Work closely with data center operations teams to implement and validate optimization strategies Research & Development * Conduct applied research on emerging ML acceleration technologies and their power/performance characteristics * Develop novel methodologies for measuring and improving energy efficiency in large-scale ML workloads * Publish findings and contribute to industry best practices in sustainable ML infrastructure

Are you a passionate scientist in the computer vision area who is aspired to apply your skills to bring value to millions of customers? Here at Ring, we have a unique opportunity to innovate and see how the results of our work improve the lives of millions of people and make neighborhoods safer. As an Applied Scientist, you will work with talented peers pushing the frontier of computer vision and machine learning technology to deliver the best experience for our neighbors. This is a great opportunity for you to innovate in this space by developing highly optimized algorithms that will work at scale. This position requires experience with developing Multi-modal LLMs and/or Vision Language Models. You will collaborate with different Amazon teams to make informed decisions on the best practices in machine learning to build highly-optimized integrated hardware and software platforms. Key job responsibilities - Participate in the design, development, evaluation, deployment and updating of data-driven models for computer vision applications. - Research and implement the state-of-the-art computer vision and Vision Language models algorithms. - Collaborate with product managers and engineering teams to design and implement computer vision and machine learning based features for Ring devices - Influence system design and product vision by making informed decisions on the selection of technology, data sources, algorithms, and sensors.

Amazon Devices is an inventive research and development company that designs and engineer high-profile devices like the Kindle family of products, Fire Tablets, Fire TV, Health Wellness, Amazon Echo & Astro products. This is an exciting opportunity to join Amazon in developing state-of-the-art techniques that bring Gen AI on edge for our consumer products. We are looking for exceptional scientists to join our Applied Science team and help develop the next generation of edge models, and optimize them while doing co-designed with custom ML HW based on a revolutionary architecture. Work hard. Have Fun. Make History. Key job responsibilities What will you do? - Quantize, prune, distill, finetune Gen AI models to optimize for edge platforms - Fundamentally understand Amazon’s underlying Neural Edge Engine to invent optimization techniques - Analyze deep learning workloads and provide guidance to map them to Amazon’s Neural Edge Engine - Use first principles of Information Theory, Scientific Computing, Deep Learning Theory, Non Equilibrium Thermodynamics - Train custom Gen AI models that beat SOTA and paves path for developing production models - Collaborate closely with compiler engineers, fellow Applied Scientists, Hardware Architects and product teams to build the best ML-centric solutions for our devices - Publish in open source and present on Amazon's behalf at key ML conferences - NeurIPS, ICLR, MLSys.

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.

Are you passionate about applying machine learning and data-driven techniques to solve real-world problems at global scale? Amazon is seeking an Applied Scientist who combines curiosity, creativity, and strong analytical skills to build models and algorithms that power customer experiences and business decisions. As an Applied Scientist I, you will work with senior scientists and engineers to design, train, and deploy ML models using large-scale datasets. You will experiment with modern techniques in supervised and unsupervised learning, natural language processing, computer vision, or optimization—depending on the team’s focus area. You’ll also have opportunities to learn Amazon’s scalable infrastructure, experiment platforms, and science best practices. This role is ideal for someone early in their career who enjoys working in collaborative, multidisciplinary teams and is excited by the opportunity to learn, innovate, and deliver measurable impact to customers. Key responsibilities include: Collaborate with scientists, engineers, and product managers to define and frame business problems as ML or optimization tasks. Build, train, and evaluate models using large, complex datasets. Implement scalable data pipelines and model-serving systems. Analyze experimental results, draw insights, and refine models to improve accuracy and robustness. Communicate findings and recommendations to technical and non-technical audiences. Continuously learn and apply new algorithms and techniques to improve existing systems.

Amazon’s Modeling and Optimization Team (MOP) is looking for a passionate individual with strong optimization and analytical skills to join us in the endeavor of designing and planning the most complex supply chain in the world. The team is responsible for optimizing the global supply chain for Amazon.com and ensuring that the company is able to inbound goods from seller and vendors, transport them to their target fulfillment center, and deliver to our customers as quickly, accurately, and cost effectively as possible. We work on problems ranging from network design to inventory management, in order to support strategic decisions. It is a terrific opportunity to have a direct impact in the business while pushing the boundaries of science. Key job responsibilities We are seeking an experienced scientist who has solid background in Operations Research, Operations Management, Applied Mathematics or other similar domain. In this role, you will develop models and solution algorithms that are innovative and scalable to solve new challenges in the network design space. You will collaborate with other scientists across teams to create integrated solutions that improves fulfillment speed, cost, and carbon emission. You have deep understanding of business challenges and provide scientific analysis to support business decision using a range of methodologies. You will also work with engineering teams to identify new data requirements, deploy new models or simplifying existing processes. About the team https://www.aboutamazon.com/news/innovation-at-amazon/how-artificial-intelligence-helps-amazon-deliver

Do you want a role with deep meaning and the ability to make a major impact? As part of Intelligent Talent Acquisition (ITA), you'll have the opportunity to reinvent the hiring process and deliver unprecedented scale, sophistication, and accuracy for Amazon Talent Acquisition operations. ITA is an industry-leading people science and technology organization made up of scientists, engineers, analysts, product professionals and more, all with the shared goal of connecting the right people to the right jobs in a way that is fair and precise. Last year we delivered over 6 million online candidate assessments, and helped Amazon deliver billions of packages around the world by making it possible to hire hundreds of thousands of workers in the right quantity, at the right location and at exactly the right time. You’ll work on state-of-the-art research, advanced software tools, new AI systems, and machine learning algorithms, leveraging Amazon's in-house tech stack to bring innovative solutions to life. Join ITA in using technologies to transform the hiring landscape and make a meaningful difference in people's lives. Together, we can solve the world's toughest hiring problems. Key job responsibilities As an Applied Scientist, you will own the design and development of end-to-end systems. You’ll have the opportunity to write technical white papers, create technical roadmaps and drive production level projects that will support Amazon Science. You will have the opportunity to design new algorithms, models, or other technical solutions whilst experiencing Amazon’s customer focused culture. The ideal scientist must have the ability to work with diverse groups of people and cross-functional teams to solve complex business problems. About the team The Automated Performance Evaluation (APE) team is a hybrid team of Applied Scientists and Software Development Engineers who develop, deploy and own end-to-end machine learning services for use in the HR and Recruiting functions at Amazon.

Passionate about books? The Kindle Unlimited team is looking for a talented Economist to help invent, design, and measure innovative science solutions to make it easier for millions of customers to find the next book they will love. Key job responsibilities In this role you will: - Partner with cross-functional teams to leverage advanced economic and causal modeling techniques, to drive business insights and decision-making. - Conduct in-depth research and analysis on large, complex data sets to understand customer behavior, pricing dynamics, and the incremental impact of business programs and initiatives. - Design, implement, and maintain scalable econometric and machine learning solutions to automate and improve key measurement and optimization capabilities. - Effectively communicate analysis, insights, and recommendations to influence senior leadership, business strategy and roadmap prioritization.

Are you a MS or PhD student interested in a 2026 internship in the field of machine learning, deep learning, generative AI, large language models and speech technology, robotics, computer vision, optimization, operations research, quantum computing, automated reasoning, or formal methods? If so, we want to hear from you! We are looking for students interested in using a variety of domain expertise to invent, design and implement state-of-the-art solutions for never-before-solved problems. You can find more information about the Amazon Science community as well as our interview process via the links below; https://www.amazon.science/ https://amazon.jobs/content/en/career-programs/university/science https://amazon.jobs/content/en/how-we-hire/university-roles/applied-science Key job responsibilities As an Applied Science Intern, you will own the design and development of end-to-end systems. You’ll have the opportunity to write technical white papers, create roadmaps and drive production level projects that will support Amazon Science. You will work closely with Amazon scientists and other science interns to develop solutions and deploy them into production. You will have the opportunity to design new algorithms, models, or other technical solutions whilst experiencing Amazon’s customer focused culture. The ideal intern must have the ability to work with diverse groups of people and cross-functional teams to solve complex business problems. A day in the life At Amazon, you will grow into the high impact person you know you’re ready to be. Every day will be filled with developing new skills and achieving personal growth. How often can you say that your work changes the world? At Amazon, you’ll say it often. Join us and define tomorrow. Some more benefits of an Amazon Science internship include; • All of our internships offer a competitive stipend/salary • Interns are paired with an experienced manager and mentor(s) • Interns receive invitations to different events such as intern program initiatives or site events • Interns can build their professional and personal network with other Amazon Scientists • Interns can potentially publish work at top tier conferences each year About the team Applicants will be reviewed on a rolling basis and are assigned to teams aligned with their research interests and experience prior to interviews. Start dates are available throughout the year and durations can vary in length from 3-6 months for full time internships. This role may available across multiple locations in the EMEA region (Austria, Estonia, France, Germany, Ireland, Israel, Italy, Jordan, Luxembourg, Netherlands, Poland, Romania, Spain, South Africa, UAE, and UK). Please note these are not remote internships.