Emine Yilmaz: An Amazon Scholar advancing the state of the art in voice shopping

Scientist leads team in London focused on improving voice-shopping experiences with Alexa.

Emine Yilmaz is a computer science professor at the University College London (UCL) and a faculty fellow at the Alan Turing Institute. Her research interests include information retrieval and natural language processing. Yilmaz is the recipient of several honors and awards in her career, including a 2018 Bloomberg Data Science Research grant for her work on building task-oriented systems, and a 2015 British Computer Society Information Retrieval Specialist Group Karen Spärck Jones Award for her research contributions in the field of information retrieval.

Emine Yilmaz, an Amazon scientist, sitting at a table with an open laptop in front of her.
Emine Yilmaz, a computer science professor at the University College London, a faculty fellow at the Alan Turing Institute, and an Amazon Scholar, is shown speaking at an Amazon Research Day event. At Amazon, Yilmaz works within the Alexa Shopping Research and Science organization.
Emine Yilmaz

Yilmaz is also an Amazon Scholar, a select group of academics who work on large-scale technical challenges for Amazon while continuing to teach and conduct research at their universities. At Amazon, Yilmaz is leading a research team based in London that’s responsible for improving the Alexa voice shopping experiences.

Given the nascency of the field—the first Echo speaker was launched six years ago—customer satisfaction in voice shopping is an open area of research. Yilmaz is uniquely positioned to drive meaningful innovations in the field. She has been involved with advancing research in modeling user behavior and predicting user satisfaction for her entire career. One example: a recent paper that Yilmaz coauthored with Manisha Verma, “Search Costs vs User Satisfaction on Mobile”, in which they studied the impact of user actions, such as inputting search queries, reading snippets, or scrolling through a search engine result page, on customer satisfaction.

Amazon Science spoke to Yilmaz about her career, her work at Amazon, and why she thinks academics will enjoy working at Amazon.

Q. What drew you to your research interests in information retrieval and natural language processing?

My interest in machine learning was sparked during my undergraduate program. As part of an assignment for a computer science class, we had to implement a machine learning algorithm that would learn to put a number of small rectangles into the smallest rectangle shape possible. I found the concept of a computer being trained to perform tasks fascinating, and decided to pursue a master’s degree in machine learning.

When I began my PhD, web search technology was newly emerging. I was intrigued by how search engines were able to retrieve results relevant to a query in a near-instantaneous manner. There were, and there still are, many open problems in the domain, and nearly all of them can be tackled using principles from machine learning. I thus decided to choose as my area of research machine learning applied to information retrieval (the computer science discipline behind search) and natural language processing.

Q. What are you working on at Amazon?

At Amazon, I’m part of the Alexa Shopping Research and Science organization headed by Yoelle Maarek. Customers interact with Alexa for a variety of shopping-related tasks—from product research to actual purchases. My team’s goal is to continually improve Alexa so that she is able to help customers no matter where they are in their shopping journey.

Q. What are some of the research problems you’re tackling at Amazon?

Annotating customer interactions with pertinent data is critical to training Alexa to get better over time. However, with billions of interactions every week, it isn’t feasible to annotate even a small percentage of those interactions manually.

Further complicating matters is the growing number of experiences that Alexa-enabled devices provide. To give just a few examples, Alexa is available on a wide range of smart speakers, tablets, smartphones, and an ever-increasing array of smart home devices. A successful customer interaction on an Echo device (adding an item to one’s shopping list) can be quite different from that on a tablet (clicking and zooming in on an image).

My team’s goal is to continually improve Alexa so that she is able to help customers no matter where they are in their shopping journey.
Emine Yilmaz, Amazon Scholar

My team applies state-of-the-art natural language processing and machine learning models to predict customer satisfaction across all of these diverse experiences. To do this, our models look at implicit criteria to evaluate whether Alexa helped customers meet their goals. These criteria include search query reformulations, how much time customers spend interacting with search results, or even whether they zoomed in to study a product image in greater detail. By studying patterns in user interactions, we are able to drive improvements to the Alexa voice shopping experience at scale.

Q. How do you see the nascent field of voice shopping evolving?

These are early days for voice shopping. That’s one of the primary reasons this is a fascinating area to be involved with. Similar to mobile phones today, I believe that intelligent voice assistants will become an embedded part of our lives. Shopping using our voice is a much more frictionless experience. Most of us speak faster than we type. With voice agents, you don’t have to take your phone out, unlock it, type out a search term and take a series of steps to complete your request. To give just one example, today you see residents of senior living centers, who would ordinarily struggle using computers, but who are using Alexa to stay connected to friends, family, and the world during COVID-19. Intelligent voice agents are going to be an integral part of our day-to-day lives. I’m really excited to be at Amazon, and have the opportunity to shape the future in how people use voice to conduct research on, and buy products.

Q. How did you come to join the Amazon Scholars program?

I received a call from an Amazon recruiter in 2019, who told me about the Amazon Scholars program. This seemed really intriguing. Indeed, to say that the entire ecosystem around Alexa is cutting edge would be a massive understatement. I was excited at the opportunity to find out more about the kind of problems the team was working on, and to see if I could contribute to their research.

I was also impressed by the investments Amazon has been making in research. At the time, Amazon had recently opened the Cambridge Development Center. They were actively hiring great talent to further innovation in multiple AI disciplines.

Career opportunities in science

See the latest Amazon job openings in machine learning, data science, and much more.

Lastly, I was drawn to working with scientists I’ve always held in high regard —be it Michael Jordan, Thorsten Joachims or Eugene Agichtein. Some of the world’s leading researchers are working as Scholars at Amazon. And given my prior work and research area interests, I was particularly interested in the work of Yoelle Maarek’s team.

Q. How do you balance your work between Amazon and University College London?

At Alexa Shopping, I’m constantly encouraged to write and publish papers at the top research conferences, both within Amazon and at my university. It certainly helps that my research areas in academia and at Amazon are distinct yet aligned. To give just one example, as part of my academic work, I recently coauthored a paper, From Stances' Imbalance to Their Hierarchical Representation and Detection , that was presented at The Web Conference in 2019. In the paper, we proposed a new approach to detecting fake news—news that purports to be factual, but which contains misstatements of fact with intention to arouse passions, attract viewership, or simply deceive. On one hand, the paper is sufficiently distinct from shopping that I can differentiate between my work in academia and at Amazon. On the other hand, the research outlined in the paper can help me invent methods towards ensuring that sellers’ descriptions on product listings are accurate.

Q. In your mind, why would academics enjoy working at Amazon?

First, the caliber of talent at Amazon is very high. I attribute this to the hiring process based on a set of Leadership Principles. The hiring process is concrete and structured, and ensures that we are always meeting a high bar when it comes to recruitment. Because the bar for hiring is so high, I’m constantly learning from my managers, from my peers, and from people who report to me.

I also think academics will readily appreciate Amazon’s “customer obsession”, one of our key Leadership Principles. In my mind, this is the primary reason academics should consider working at the company. Throughout my career, when I’ve thought about research, I’ve also thought about the end application. At Amazon, you have the opportunity to have a positive impact on the lives of millions of people. Staying focused on the customer and working a solution backward makes our research a lot more fulfilling. It also keeps you grounded, and prevents you from drifting into irrelevance, both in academia and within the industry.

Related content

US, WA, Bellevue
Does the idea of creating technology solutions for delivering 11 Billion+ packages across the globe excite you? If yes, come join a fun-loving, diverse, and creative team at Amazon Last Mile! The vision of the team is "To create Earth’s safest, most adaptive, and efficient plans for Last Mile logistics". The Last Mile Delivery Technology team is instrumental in impacting customer satisfaction directly, by devising innovative ways to deliver packages quickly and cost-effectively to the customers, and at scale using Artificial Intelligence (AI), Machine Learning and Operations Research solutions. Last Mile Delivery Technology organization supports the design, planning and execution of last mile transportation for Amazon’s various parcel and grocery delivery programs. All these programs require a large number of decision support systems to operate at scale and serve our customers, spanning demand planning, jurisdiction planning, delivery channel and network design, capacity planning for on the road and under the roof at delivery stations, routing inputs and route optimization. While these decision support systems have thus far been approached through the lens of traditional optimization and machine learning, we are looking to re-envision this space and pursue Foundational AI research, to innovate and advance the state of these decision support systems. Specifically, we are looking to develop foundational models (including Large Language Models, Multimodal Language Models, Multimodal Models), and adaptations to serve last mile use cases. Beyond Amazon the work developed will spur new fundamental knowledge and innovation in the logistics space. Job Location : Bellevue WA or Austin TX. Key job responsibilities You have deep expertise in ML/AI, staying current with the latest research and techniques. You also invent or adapt new scientific approaches based on customer needs, producing high-quality research reports and contributing to peer-reviewed publications when appropriate You are a highly skilled software engineer whose work is consistently of high quality, meets industry standards, and incorporates best practices. You work semi-autonomously, contribute to operational excellence. You have strong interpersonal and leadership skills, effectively collaborating with your team, championing scientific advancements, onboarding new teammates, setting a high standard for your scientific contributions, and actively participating in the wider scientific community
US, WA, Seattle
The Worldwide Defect Elimination (WWDE) Science team in Amazon Customer Service builds state-of-the-art Artificial Intelligence (AI) models to enable defect-free shopping experiences for Amazon customers. We develop technology and mechanisms to discover, root cause, measure, and escalate defects for resolution before they impact a broader range of customers. We are looking for a creative problem solver and technically-skilled Research Scientist able and interested in building AI solutions to address customer issues at scale. The ideal candidate will lead the development of innovative solutions that identify, root cause, attribute, and summarize problems embedded in large volumes of customer feedback in different modalities. They will also utilize the latest advances in GenAI technology to explore billions of customer contacts and automate defect resolution workflows. As a part of this role, this candidate will collaborate with a large team of experts in the field and move the state of defect elimination research forward. This candidate should have a knack for leveraging AI to translate complex data insights into actionable strategies and can communicate these effectively to both technical and non-technical audiences. Key job responsibilities * Apply science models to extract actionable information from large volumes and varying modalities of customer feedback * Leverage GenAI/Large Language Model (LLM) technology for scaling and automating defect elimination workflows * Design and implement metrics to evaluate the effectiveness of AI models * Present deep dives and analysis to both technical and non-technical stakeholders, ensuring clarity and understanding and influencing business partners * Perform statistical analysis and statistical tests including hypothesis testing and A/B testing * Recognize and adopt best practices in reporting and analysis: data integrity, test design, analysis, validation, and documentation A day in the life If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply! Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include: 1. Medical, Dental, and Vision Coverage 2. Maternity and Parental Leave Options 3. Paid Time Off (PTO) 4. 401(k) Plan About the team The Worldwide Defect Elimination (WWDE) team's mission is to understand and resolve all issues impacting customers at scale. The WWDE Science team is a force multiplier within this group, helping to to apply science solutions to eliminate defects and enhance customer experience.
US, TX, Austin
The Automated Reasoning Group in AWS Utility Computing is looking for a Senior Applied Scientist with experience in building scalable automated reasoning solutions that delight customers. You will be part of a world-class team building the next generation of automated reasoning tools and services. You will apply your knowledge to propose solutions, create software prototypes, and develop prototypes into production systems using software development tools. In addition, you will support and scale your solutions to meet the ever-growing demand of customer use. You have demonstrated leadership in automated reasoning positions in industry or academia, strong verbal and written communication skills, are self-driven and deliver high quality results in a fast-paced environment. Each day, hundreds of thousands of developers make billions of transactions worldwide on AWS. They harness the power of the cloud to enable innovative applications, websites, and businesses. Using automated reasoning technology and mathematical proofs, AWS allows customers to answer questions about security, availability, durability, and functional correctness. We call this provable security, absolute assurance in security of the cloud and in the cloud. https://aws.amazon.com/security/provable-security/ Key job responsibilities As a Senior Applied Scientist, you will help shape the definition and vision for applied science across teams within AWS. We have a diverse portfolio of projects that target protocol, code, and hardware verification, and leadership opportunities exist for: - Advance automated code-level reasoning and invariant synthesis and proof repair for cloud-scale web services. - Build new engines and extending foundational proof engines that apply to distributed systems. - Researching the application of automated reasoning to novel software applications. - Building automated reasoning solutions for critical AWS DSLs for architectural configuration, migration, code generation, and other areas. - Improving integration and user experience of tools to support large-scale adoption and use of automated reasoning techniques. You will work in an agile, startup-like development environment, where you are always working on the most important things, and you will design, implement, test, deploy and maintain innovative software solutions to transform service performance, durability, cost, and security. About the team About AWS Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the preferred 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. This team is part of AWS Utility Computing: Utility Computing (UC) 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.
AE, Dubai
Are you looking to work at the forefront of Machine Learning and AI? Would you be excited to apply cutting edge Generative AI algorithms to solve real world problems with significant impact? The Generative AI Innovation Center at AWS is a new strategic team that helps AWS customers implement Generative AI solutions and realize transformational business opportunities. This is a team of strategists, data scientists, engineers, and solution architects working step-by-step with customers to build bespoke solutions that harness the power of generative AI. The team helps customers imagine and scope the use cases that will create the greatest value for their businesses, select and train the right models, define paths to navigate technical or business challenges, develop proof-of-concepts, and make plans for launching solutions at scale. The GenAI Innovation Center team provides guidance on best practices for applying generative AI responsibly and cost efficiently. You will work directly with customers and innovate in a fast-paced organization that contributes to game-changing projects and technologies. You will design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience. We’re looking for ML Data Scientists capable of using GenAI and other techniques to design, evangelize, and implement state-of-the-art solutions for never-before-solved problems. Key job responsibilities As an ML Data Scientist, you will * Collaborate with ML scientist and architects to Research, design, develop, and evaluate cutting-edge generative AI algorithms to address real-world challenges * Interact with customers directly to understand the business problem, help and aid them in implementation of generative AI solutions, deliver briefing and deep dive sessions to customers and guide customer on adoption patterns and paths to production * Create and deliver best practice recommendations, tutorials, blog posts, sample code, and presentations adapted to technical, business, and executive stakeholder * Provide customer and market feedback to Product and Engineering teams to help define product direction
US, WA, Bellevue
We are seeking a passionate, talented, and inventive individual to join the Applied AI team and help build industry-leading technologies that customers will love. This team offers a unique opportunity to make a significant impact on the customer experience and contribute to the design, architecture, and implementation of a cutting-edge product. The mission of the Applied AI team is to enable organizations within Worldwide Amazon.com Stores to accelerate the adoption of AI technologies across various parts of our business. We are looking for a Senior Applied Scientist to join our Applied AI team to work on LLM-based solutions. We are seeking an experienced Scientist who combines superb technical, research, analytical and leadership capabilities with a demonstrated ability to get the right things done quickly and effectively. This person must be comfortable working with a team of top-notch developers and collaborating with our research teams. We’re looking for someone who innovates, and loves solving hard problems. You will be expected to have an established background in building highly scalable systems and system design, excellent project management skills, great communication skills, and a motivation to achieve results in a fast-paced environment. You should be somebody who enjoys working on complex problems, is customer-centric, and feels strongly about building good software as well as making that software achieve its operational goals. Key job responsibilities You will be responsible for developing and maintaining the systems and tools that enable us to accelerate knowledge operations and work in the intersection of Science and Engineering. You will push the boundaries of ML and Generative AI techniques to scale the inputs for hundreds of billions of dollars of annual revenue for our eCommerce business. If you have a passion for AI technologies, a drive to innovate and a desire to make a meaningful impact, we invite you to become a valued member of our team. A day in the life On our team you will push the boundaries of ML and Generative AI techniques to scale the inputs for hundreds of billions of dollars of annual revenue for our eCommerce business. If you have a passion for AI technologies, a drive to innovate and a desire to make a meaningful impact, we invite you to become a valued member of our team.
US, WA, Seattle
We’re working to improve shopping on Amazon using the conversational capabilities of large language models, and are searching for pioneers who are passionate about technology, innovation, and customer experience, and are ready to make a lasting impact on the industry. You'll be working with talented scientists and engineers to innovate on behalf of our customers. If you're fired up about being part of a dynamic, driven team, then this is your moment to join us on this exciting journey! Key job responsibilities We seek strong Applied Scientists with domain expertise in machine learning and deep learning, transformers, generative models, large language models, computer vision and multimodal models. You will devise innovative solutions at scale, pushing the technological and science boundaries. You will guide the design, modeling, and architectural choices of state-of-the-art large language models and multimodal models. You will devise and implement new algorithms and new learning strategies and paradigms. You will be technically hands-on and drive the execution from ideation to productionization. You will work in collaborative environment with other technical and business leaders, to innovate on behalf of the customer.
US, MA, Westborough
Are you inspired by invention? Is problem solving through teamwork in your DNA? Do you like the idea of seeing how your work impacts the bigger picture? Answer yes to any of these and you’ll fit right in here at Amazon Robotics. We are a smart team of doers that work passionately to apply cutting edge advances in robotics and software to solve real-world challenges that will transform our customers’ experiences in ways we can’t even imagine yet. We invent new improvements every day. We are Amazon Robotics and we will give you the tools and support you need to invent with us in ways that are rewarding, fulfilling and fun. Amazon Robotics is seeking Applied Science Interns and Co-ops with a passion for robotic research to work on cutting edge algorithms for robotics. Our team works on challenging and high-impact projects within robotics. Examples of projects include allocating resources to complete a million orders a day, coordinating the motion of thousands of robots, autonomous navigation in warehouses, identifying objects and damage, and learning how to grasp all the products Amazon sells. As an Applied Science Intern/Co-op at Amazon Robotics, you will be working on one or more of our robotic technologies such as autonomous mobile robots, robot manipulators, and computer vision identification technologies. The intern/co-op project(s) and the internship/co-op location are determined by the team the student will be working on. Please note that by applying to this role you would be considered for Applied Scientist summer intern, spring co-op, and fall co-op roles on various Amazon Robotics teams. These teams work on robotics research within areas such as computer vision, machine learning, robotic manipulation, navigation, path planning, perception, optimization and more. Learn more about Amazon Robotics: https://amazon.jobs/en/teams/amazon-robotics
IL, Tel Aviv
Are you a MS or PhD student interested in a 2024 Research Science Internship, where you would be using your experience to initiate the design, development, execution and implementation of scientific research projects? If so, we want to hear from you! Is your research in machine learning, deep learning, automated reasoning, speech, robotics, computer vision, optimization, or quantum computing? If so, we want to hear from you! We are looking for motivated students with research interests in a variety of science domains to build 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 Key job responsibilities As a Research Science Intern, you will have following key job responsibilities; • Work closely with scientists and engineering teams (position-dependent) • Work on an interdisciplinary team on customer-obsessed research • Design new algorithms, models, or other technical solutions • Experience Amazon's customer-focused culture A day in the life At Amazon, you will grow into the high impact, visionary 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 and up to 12 months for part time internships. This role may available across multiple locations in the EMEA region (Austria, Estonia, France, Germany, Ireland, Israel, Italy, Luxembourg, Netherlands, Poland, Romania, Spain, UAE, and UK). Please note these are not remote internships.
US, WA, Seattle
Join us in building on AWS, for AWS! Amazon Web Services (AWS) provides companies of all sizes with an infrastructure web services platform in the cloud (“Cloud Computing”). With AWS you can requisition compute power, storage, and many other services – gaining access to a suite of elastic IT infrastructure services as your business demands them. AWS is the leading platform for designing and developing applications for the cloud and is growing rapidly with hundreds of thousands of companies in over 190 countries on the platform. Developers all over the world rely on our storage, compute, and virtualized services. Our success depends on our world-class selling and field teams, and these teams rely on the Worldwide Sales Strategy and Operations (SMGS Ops) team to power their activities. We’re handling massive scale, providing data that drives the AWS business internally, and delivering products and services to help our Amazon Web Service selling teams, marketing groups, and customers. We’re looking for a Data Scientist to design and deliver solutions that combine machine learning, human-in-the-loop input, and distributed big data technologies. We're building a cutting-edge data platform to enable us to arm our field teams with the actionable intelligence needed to engage and serve every possible AWS customer in the world, to the fullest. This position may be based in Seattle, WA; Dallas, TX Key job responsibilities - Design solutions to complex and ambiguous data challenges, starting from first principles - Apply Machine Learning to solve data problems, such as record matching, at scale - Leverage company data from third-party sources in combination with internal AWS data to develop quantitative models answering critical business questions - Build human-in-the-loop workflows, to complement and augment ML solutions - Work with AWS machine learning and big data technologies such as Amazon Sagemaker, EMR, S3, DynamoDB, Lambda, and more - Experiment and explore new technologies to create innovative solutions - Use Natural Language Processing and language models to derive insights from unstructured sources like public company regulatory filings and annual reports About the team Here at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and we host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon’s culture of inclusion is reinforced within our 14 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust. Our team also puts a high value on work-life balance. Striking a healthy balance between your personal and professional life is crucial to your happiness and success here, which is why we aren’t focused on how many hours you spend at work or online. Instead, we’re happy to offer a flexible schedule so you can have a more productive and well-balanced life—both in and outside of work. About AWS Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the preferred 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.
US, WA, Bellevue
The AGI Data Service team is seeking a dedicated, skilled, and innovative Scientist with a robust background in deep learning, to build industry-leading technology with Large Language Models (LLMs) and multimodal systems. Key job responsibilities As part of the AGI-DS team, a Research Scientist will collaborate closely with talented colleagues to lead the development of advanced approaches and modeling techniques, driving forward the frontier of LLM technology. This includes innovating model-in-the-loop and human-in-the-loop approaches to ensure the collection of high-quality data, safeguarding data privacy and security for LLM training, and more. A scientist will also have a direct impact on enhancing customer experiences through state-of-the-art products and services that harness the power of speech and language technology. A day in the life The Scientist with the AGI team will support the science solution design, run experiments, research new algorithms, and find new ways of optimizing the customer experience; while setting examples for the team on good science practice and standards. Besides theoretical analysis and innovation, the scientist will also work closely with talented engineers and scientists to put algorithms and models into practice. The ideal candidate should be passionate about delivering experiences that delight customers and creating robust solutions. They will also create reliable, scalable and high-performance products that require exceptional technical expertise, and a sound understanding of Machine Learning.