Careers

The Artificial General Intelligence (AGI) team is looking for a Senior Applied Scientist to work on pre-training methodologies for Generative Artificial Intelligence (GenAI) models. You will 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 Amazon, working with other acclaimed engineers and world-famous scientists. Key job responsibilities Join us to work as an integral part of a team that has diverse experience with GenAI models in this space. We work on these areas: - Scaling laws - Hardware-informed efficient model architecture, low-precision training - Optimization methods, learning objectives, curriculum design - Deep learning theories on efficient hyperparameter search and self-supervised learning - Reasoning, self-reflection, interactive learning, data synthesis - Distributed training methods and solutions About the team The AGI team has a mission to push the envelope in LLMs and multimodal systems, in order to provide the best-possible experience for our customers.

Alexa International Tech (AIT) team is looking for a passionate, talented, and inventive sr language data Scientist to help build industry-leading technology with Large Language Models (LLMs) and multimodal systems, requiring strong deep learning and generative models knowledge. You will collaborate with fellow language data scientists, program managers, as well as stakeholders in science, engineering, and product teams to understand the role data plays in developing data sets and exemplars that meet customer needs. You will analyze and automate processes for collecting and annotating LLM inputs and outputs to assess data quality and measurement. You will apply state-of-the-art Generative AI techniques to analyze how well our data represents human language and run experiments to gauge downstream interactions. You will work collaboratively with other language data scientists and scientists to design and implement principled strategies for data optimization. Key job responsibilities Collaborate with Scientists and Software Engineers to help design APIs and evaluate performance of LLM Produce and manipulate different types of language data, analyze, and provide efficient solutions Design and lead a data collection; define scope and target, provide a guideline and training, guide teams cross sites to meet the quality bar, and run evaluation of data for hand off Engineer prompts to guide generative AI to produce desired outputs in context Automate operations and perform data analysis using python, or other scripting language. Advocate strict adherence to annotation guidelines Test and deploy changes to Alexa's language understanding codebase Identify and solve production issues that are impacting the Alexa customer experience, Collaborate with other linguists, scientists and designers in creating optimal solutions to elevate the customer experience Own the customer-facing machine learning and deterministic models for a specific domain of features Use modeling tools to bootstrap and test new functionalities

Alexa International Tech (AIT) team is looking for a passionate, talented, and inventive Applied Scientist to help build industry-leading technology with Large Language Models (LLMs) and multimodal systems, requiring strong deep learning and generative models knowledge. Key job responsibilities As an Applied Scientist with the AIT team, you will work with talented peers to develop novel algorithms and modeling techniques to advance the state of the art with LLMs. Your work will directly impact our international customers in the form of products and services that make use of digital assistance technology. You will leverage Amazon’s heterogeneous data sources, unique but diverse international customer nuances and large-scale computing resources to accelerate advances in voice domain in multi-modal setup. The ideal candidate possesses a solid understanding of machine learning fundamentals and a passion for pushing boundaries in this vast and quickly evolving field. They thrive in fast-paced environments to will tackle complex challenges, and excel at swiftly delivering impactful solutions while iterating based on user feedback. A day in the life · Analyze, understand, and model customer behavior and the customer experience based on large scale data. Especially showing passion towards solving for international customer-centric challenges. · Build novel online & offline evaluation metrics an methodologies for personal digital assistants and customer scenarios, on multi-modal devices. · innovate and deliver deep learning based innovation across life-cycle such as policy-based learning, international customer specific model performance tuning. · Quickly experiment and setup experimentation framework for agile model and data analysis or A/B testing · Contribute through industry first research to drive the innovation forward.

Alexa International Tech (AIT) team is looking for a passionate, talented, and inventive Sr language Data Scientist to help build industry-leading technology with Large Language Models (LLMs) and multimodal systems, requiring strong deep learning and generative models knowledge. You will collaborate with fellow Language Data Scientists, Program managers, as well as Stakeholders in science, engineering, and product teams to understand the role data plays in developing data sets and exemplars that meet customer needs. You will analyze and automate processes for collecting and annotating LLM inputs and outputs to assess data quality and measurement. You will apply state-of-the-art Generative AI techniques to analyze how well our data represents human language and run experiments to gauge downstream interactions. You will work collaboratively with other language data scientists and scientists to design and implement principled strategies for data optimization. Key job responsibilities Collaborate with Scientists and Software Engineers to help design APIs and evaluate performance of LLM Produce and manipulate different types of language data, analyze, and provide efficient solutions Design and lead a data collection; define scope and target, provide a guideline and training, guide teams cross sites to meet the quality bar, and run evaluation of data for hand off Engineer prompts to guide generative AI to produce desired outputs in context Automate operations and perform data analysis using python, or other scripting language. Advocate strict adherence to annotation guidelines Test and deploy changes to Alexa's language understanding codebase Identify and solve production issues that are impacting the Alexa customer experience, Collaborate with other linguists, scientists and designers in creating optimal solutions to elevate the customer experience Own the customer-facing machine learning and deterministic models for a specific domain of features Use modeling tools to bootstrap and test new functionalities

The Sr. Applied Scientist will be responsible for building advanced forecasting models for Amazon Devices using the latest machine learning and deep learning techniques. They will develop scalable, accurate predictive models to drive key decision making that supports critical business decisions (including pricing, promotions and supply chain) for all of Amazon consumer hardware product lines WW. Collaborating with cross-functional teams, they will integrate these models into operational systems to enhance data-driven decision-making and optimize business outcomes. A strong focus on applying cutting-edge ML/DL methodologies and a passion for innovation will be key to success in this role. Key job responsibilities - Build and implement advanced forecasting models using machine learning techniques such as transfer learning, neural networks, and time series models, driving decisions for pricing, promotions, and supply chain optimization. - Write efficient, scalable production code (Python or equivalent) to develop and productionalize models using frameworks like TensorFlow, PyTorch, and scikit-learn, collaborating with data engineers to ensure smooth deployment into real-time systems. - Continuously optimize models through techniques like hyperparameter tuning, feature engineering, and cross-validation, leveraging tools such as TensorFlow and Keras to improve performance and scalability. - Communicate complex model results and insights using data visualization tools (e.g., Matplotlib, Seaborn) and provide actionable recommendations to cross-functional teams for pricing, promotions, and supply chain strategies.

We are seeking a highly talented Applied Scientist to join our MENA Science team and drive the development of state-of-the-art machine learning solutions for our customers in the MENA region. In this role, you will leverage state-of-the-art machine learning and data science techniques to create cutting-edge solutions that directly address critical customer problems. Your work will directly impact the customer experience and profitability of our MENA businesses, helping us enhance catalog quality, improve machine translation, prevent abuse and fraud etc. Key job responsibilities • Invent, implement, and deploy cutting-edge machine learning algorithms and models to solve complex, real-world problems for our MENA customers. • Collaborate closely with cross-functional teams, including product managers, engineers, and other applied scientists, to identify high-impact areas for innovation. • Prototype and test new approaches, such as leveraging large language models (LLMs) and other advanced techniques, to drive measurable improvements in key business metrics. • Tackle a diverse range of challenges, such as improving catalog quality through large language models, enhancing machine translation, developing abuse prevention systems etc. • Staying up-to-date with the latest advancements in machine learning and data science, and proactively identifying opportunities to apply these techniques to drive business impact. • Contribute to the broader scientific community by publishing your work at top-tier conferences and journals. A day in the life Diving deep in to ambiguous and complex business problems and translating them to appropriate ML problem statements. Applying relevant science solutions for the ML problems. Staying abreast with evolving science landscape and applying the state-of-the-art. About the team MENA tech is a 200 people tech organization spread across Jordan, UAE, India and Seattle, building amazing solutions for customers in the region. We deploy in MENA first but build for the world.

As a Principal Applied Scientist, you are a trusted part of the technical leadership. You bring business and industry context to science and technology decisions. You set the standard for scientific excellence and make decisions that affect the way we build and integrate algorithms. You solicit differing views across the organization and are willing to change your mind as you learn more. Your artifacts are exemplary and often used as reference across organization. You are a hands-on scientific leader. Your solutions are exemplary in terms of algorithm design, clarity, model structure, efficiency, and extensibility. You tackle intrinsically hard problems, acquiring expertise as needed. You decompose complex problems into straightforward solutions. You amplify your impact by leading scientific reviews within your organization or at your location. You scrutinize and review experimental design, modelling, verification and other research procedures. You probe assumptions, illuminate pitfalls, and foster shared understanding. You align teams toward coherent strategies. You educate, keeping the scientific community up to date on advanced techniques, state of the art approaches, the latest technologies, and trends. You help managers guide the career growth of other scientists by mentoring and play a significant role in hiring and developing scientists and leads. Key job responsibilities - Responsible for defining key research directions, adopting or inventing new machine learning techniques, conducting rigorous experiments, publishing results, and ensuring that research is translated into practice. - Develop long-term strategies, persuade teams to adopt those strategies, propose goals and deliver on them. - Participate in organizational planning, hiring, mentorship and leadership development. - Technically ambitious with a passion for building scalable science and engineering solutions. - You will serve as a key scientific resource in full-cycle development (conception, design, implementation, testing to documentation, delivery, and maintenance). About the team Want to be part of the team whose mission is to expand Alexa to new countries, languages, devices and cultures? The Alexa International team makes it happen. Our customers are very diverse in where they live, the languages they speak to Alexa, the devices they use and the content that matters most. In turn our problems are diverse and need innovative solutions. Alexa International is at the nexus of all other Alexa teams and features, such as Smart Home, Music, News, ASR (Automatic Speech Recognition), NLU (Natural Language Understanding), Fire TV, Skills etc. We collaborate with hardware and software developers within and outside Amazon to build delightful experience for our customers. We’re working hard, having fun, and making history; come join us!

Our mission is to build best-in-class, product-based compliance solutions harnessing the power of state-of-the-art multilingual, multimodal, LLMs, and generative AI to improve productivity and elevate user experiences. We develop these solutions as foundational multi-use ML services that eliminate compliance friction for our partners, reduce operational costs, and ensure a great buyer experience, while enabling extensions beyond compliance to non-compliance use cases Amazon wide. As a Manager, Applied Science in Compliance Shared Services (CoSS) Romania Applied Research & Development Center, you will lead scientists in applying state-of-the-art unstructured data validation and processing approaches to develop ML primitives that enable Amazon to process unstructured content, such as document and images, at Amazon scale. You will lead the science vision, roadmap, and customer working backwards, while partnering with technology and product partners to enable our best-in-class ML algorithms and solutions to be easily adopted and integrated into customer technology stacks to maximize business impact for Amazon. You will develop mechanisms that not just deliver results but also foster growth and innovation among scientists, and contribute to developing CoSS Romania Applied Research and Development Center into a world-class applied research organization internally within Amazon and externally in tier 1 science conferences. A successful candidate is passionate about driving innovation and shaping the future of e-commerce, spearheading the development of innovative, ML, LLM and generative AI-driven solutions, and being a trusted role model who can energize our cross-functional team of scientists, engineers, product and business leaders to persevere through challenges and setbacks to achieve impactful results on behalf of our customers. Key job responsibilities Lead Science Vision and Roadmap – Own and drive team charter, working backwards from customer problems and product strategy, to develop a long-term science vision and plan, team tenets, and contribute to organizational working backwards documents (e.g. press release, FAQs). Execution of Science Roadmap – Including goals and supporting VP-level business goals. Develop mechanisms that enable team to collaborate on research, deliver independently, and integrate with e2e process and upstream and downstream technology and business dependencies. Insist on a high bar for deliveries with monitoring and audit mechanisms for your team's solutions. Lead Science Brand internally and externally – Work with CoSS Product and leaders to expose science innovations to other organizations. Develop the CoSS Romania Applied Research and Development Center as a recognized brand for high quality AI research and ML products. Plan research roadmap to submit and publish in external tier 1 conferences. Hire, develop and nurture scientists - Grow and develop scientists, both direct reports and others in organization, in not just hard science and technical skills and competencies, but also leadership principles and collaborations with other scientists and project team members to grow their ability to increase scope, impact and influence at Amazon. A day in the life 10:00 am - Team stand-up 10:30 am - Review/drive key projects with scientists in team. 12:00 pm - Lunch with team and/or partners in the CoSS Romania Applied Research and Development Center 1:00 pm - Meet with EU business teams, and other tech partners on dependencies, status, and dates for a key project. 2:00 pm - Prepare for a demo with a potential customer 3:00 pm - 1:1s with team 3:30 pm - Continue writing a document for a new team product and research direction. 5:00 pm - Meet with US leaders - principal scientist, manager, and Product team, as well as other CoSS or business partners in the US. 6:00 pm - Project meeting with US partners. 7:00 pm - Last minute escalation - clarify team's responsibilities with a US TPM. 7.30 pm - End - Go home for dinner.

Are you excited about the prospect of making it easier for builders to innovate and create great software? If so, Amazon Software Builder Experience (ASBX) may be the place for you. Created in 2022, ASBX has the mission of creating the world’s best builder experience across tens of thousands of software engineers across both Amazon and AWS. Builder Insights works at the core of ASBX, shaping what it means to create the world’s best software builder experience. How do we reduce friction and toil for builders, enabling them to have more time to build features and capabilities that will delight Amazon’s customer? Where should we invest in tooling, automation, knowledge discovery, training, etc. to create the biggest benefits for builders? How do we inform managers what “good” looks like compared to teams similar to them? These are just a few of the challenges we are tackling right now. We are looking for a passionate and hardworking scientist to use data to discover insights and turn those insights into actionable recommendations and products that improve the experience of builders across Amazon. As a data scientist on the Builder Insights team, you will help conduct rigorous science for the organization, with a focus on discovery, research, and application of generated insights into science-enabled products and features. You will have exposure to senior leadership as we communicate results and provide scientific guidance to the business. This role will also collaborate with scientists across organizations to influence science roadmaps and disseminate research. You will work with engineers to onboard data, perform scientifically rigorous insight discovery and research, and develop the right statistical and machine learning model-based solutions to deliver impact for builders. You will solve ambiguous problems, working with stakeholders to determine the right questions to ask and developing the roadmap for delivering results. You will apply analytical abilities, business understanding, and technical expertise to identify specific and actionable opportunities to solve existing business problems and look around corners for future opportunities. You will synthesize and communicate insights and recommendations to audiences of varying levels of technical sophistication to influence investment into builder experience improvements through data-backed solutions. 10025 Key job responsibilities • Lead projects, requiring both business and technical domain knowledge, and drive solutions to complex or ambiguous problems with limited guidance. • Create models and analyses that affect important business decisions. • Review analyses of other scientists and provide feedback. • Employ scientifically rigorous standards across multiple data science disciplines, knowing what trade-offs to make to deliver results. • Build models using Python, R, etc. (and ability to access data using Spark, SQL, or similar) • Proficiently use at least one common data science language to develop models (Python, R, etc.) and process data (Spark, SQL, etc.). • Communicate verbally and in writing to business customers with various levels of technical knowledge, educating them about our systems, as well as sharing insights and recommendations About the team The data science team in Builder Insights believes Are Right, A Lot means listening to diverse points of view and building a culture of inclusivity where every team member can contribute. It's only when we work together and include everyone that the best ideas can shine through, and that's when we have the most impact for our customers. You can let your Ownership shine on this team! - we wear different hats, getting involved with product strategy, building infrastructure, and everything in between. We have an innate desire to Learn & Be Curious and Dive Deep as engineers and scientists. AWS Utility Computing (UC) provides product innovations — from foundational services such as Amazon’s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS’s services and features apart in the industry. As a member of the UC organization, you’ll support the development and management of Compute, Database, Storage, Internet of Things (Iot), Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for their cloud services. Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Mentorship & Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. Hybrid Work We value innovation and recognize this sometimes requires uninterrupted time to focus on a build. We also value in-person collaboration and time spent face-to-face. Our team affords employees options to work in the office every day or in a flexible, hybrid work model near one of our U.S. Amazon offices.

At Amazon's FinTech organization, we are seeking a Senior Applied Scientist to spearhead the development of cutting-edge Generative AI applications that will redefine the financial services industry. You will harness the transformative power of Large Language Models (LLMs) and multi-agent architectures to drive disruptive innovation across Finance domains such as fraud prevention, financial forecasting, and insurance. Because of our scale, your products will have hundreds of millions of dollars of impact. You will collaborate closely with cross-functional business and engineering teams to identify and deliver high-impact use cases for Generative AI. You will design, develop, and evaluate Generative AI models and agents. You will partner with engineering teams to ensure seamless model deployment and integration into production systems, while also driving continued scientific innovation as a published thought leader and practitioner. You will mentor and develop junior scientists and engineers, fostering a culture of continuous learning and improvement. You will contribute to the broader research community by publishing your work in peer-reviewed conferences and journals. Check out this AWS Blog for some of our recent work in LLMs for financial application: https://aws.amazon.com/blogs/machine-learning/efficient-continual-pre-training-llms-for-financial-domains/ Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in our careers.