The science behind Echo Frames

How the team behind Echo Frames delivered longer battery life and improved sound quality inside the slim form factor of a pair of eyeglasses.

When the team behind Amazon’s Echo Frames set out to improve the next generation of their product, they needed to strike a delicate balance. Customer feedback on earlier versions of the smart audio eyeglasses centered on three elements: longer battery life, more style options, and improved sound quality.

A man with a beard is seen wearing a pair of Echo Frames glasses. He is standing outside and is pictured in three-quarters view.
Echo Frames feature custom-built speech processing technology that drastically improves word recognition — key for interacting with Alexa in windy or noisy environments.

Achieving all three of those goals would be a challenge in itself; doing that inside the slim form factor of a pair of Alexa-enabled eyeglasses upped the ante.

“All three of those goals are in tension with one another,” says Adam Slaboski, senior manager of product management and product lead for Echo Frames. The easiest way to improve battery and audio would be to increase the size of the device, but that would conflict with feedback around the importance of design. Amping up bass to improve the audio experience would consume more battery, and so on.

Finding that sweet spot was a huge effort in engineering and customer understanding.
Adam Slaboski

“Finding that sweet spot was a huge effort in engineering and customer understanding," Slaboski says.

With Echo Frames (3rd Gen) and Carrera Smart Glasses with Alexa (designed in collaboration with Safilo, one of the world’s leading eyewear companies), the Smart Eyewear team met the challenge.

The smart glasses feature enhanced audio playback, with custom-built speech-processing technology that dramatically improves word recognition — key for interacting with Alexa in windy or noisy environments. The new range of frame styles come in a variety of sizes, and all come with a significant boost in battery life.

From the outside, Echo Frames still look like a pair of regular eyeglasses. “But we changed everything on the inside,” says Jean Wang, general manager and director of Smart Eyewear. “And we learned new lessons along the way.”

Here’s how Amazon engineers and product designers tackled all three customer demands.

Turning up the volume with open-ear audio

Like previous generations of Echo Frames, the current model uses open-ear audio. In addition to fitting the form factor of a pair of glasses, this allows users to maintain awareness of their surroundings while interacting with Alexa or enjoying audio entertainment.

Related content
Combining psychoacoustics, signal processing, and speaker beamforming enhances stereo audio and delivers an immersive sound experience for customers.

The open-ear audio design has been popular with users who are blind or have low vision, notes Jenai Akina, senior product manager for Echo Frames. “It’s really beneficial that it doesn’t obstruct a critical sense like hearing,” she explains. “That form factor is really helpful for daily interactions — especially when we want to be open to engage with our environment and the people around us. Open ear allows customers to maintain awareness, while providing access to a voice assistant.”

Open-ear audio brings a host of unique challenges to the engineering process. Typical headphones and earbuds block off the ear from the outside world, preventing air from escaping. That funnels more of the sound waves from the speakers into the user’s ears. With an open-ear design, sound has to travel farther, and there is less control over direction. That could lower the audio volume and reduce clarity — and importantly, audio could leak out to people standing nearby. The key is to drive the sound pressure as much as possible toward the user’s ears while minimizing the audio leakage.

By bringing people into the lab, we can simulate real environmental noise conditions like wind, background noise in a crowded restaurant, and the sound of cars on the road.
Scott Choi

In working to improve audio quality, the team continued to hone the directionality of the sound while also working to improve volume and bass. A technique called dipole speaker configuration helps to do both. In addition to a sound porthole located near the ear canal, the frames feature a second porthole that cancels unnecessary sound while amping up bass.

With input from in-house audio experts and instruments to analyze measurements like harmonic distortion, the team came up with a set of potential tuning solutions that met objective targets for audio quality. They then tested those “flavors” of tuning in the lab with several user groups.

“By bringing people into the lab, we can simulate real environmental-noise conditions like wind, background noise in a crowded restaurant, and the sound of cars on the road,” explains senior manager of audio Scott Choi. That allowed his team to understand environmental variables in a controlled setting.

With the feedback from those focus groups, the team then selected a few of the most popular tunings to push out to beta testing, where users could provide feedback on a weekly basis.

“We see how the feedback trends change with each tuning change, which gradually allows it to mature and converge into a certain tuning,” Choi says. The result is audio calibrated to maximize intelligibility and volume without leaking private conversations (or guilty-pleasure playlists).

The Echo Frame team used a rotating arch of microphones to lest leakage. This animation shows the array moving in circles around a mannequin wearing the Gen 3 prototype, creating a 3D sphere plot of audio leakage. Via this testing, the team was able to minimize leakage to the side and back.
The Echo Frame team used a rotating arch of microphones to lest leakage. The array moved in circles around a mannequin wearing the Gen 3 prototype, creating a 3D sphere plot of audio leakage. Via this testing, the team was able to minimize leakage to the side and back.

To test leakage, the audio team rigged up a rotating arch of microphones. The array moved in circles around a mannequin wearing the Gen 3 prototype, creating a 3-D sphere plot of audio leakage. Choi explains that they focused on minimizing leakage to the side and back, and ultimately, the speakers were moved much closer to the ear to help minimize leakage and improve loudness.

Leakage isn’t the only privacy consideration. The Echo Frame team also continues to innovate on protecting users from bad actors who may get hold of their smart glasses.

Related content
Amazon senior principal engineer Luu Tran is helping the Alexa team innovate by collaborating closely with scientist colleagues.

Gen 2 protected users by requiring them to authenticate their sessions using a trusted phone. Without authentication, a user can’t invoke sensitive commands like “navigate me home,” unlocking a smart lock, or making a purchase. But customers didn’t like the added friction.

Now customers who enroll in Alexa Voice ID will be able to use their vocal fingerprints for authentication to receive responses to smart-home utterances.

“We’re the first on-the-go Alexa device to use Voice ID for privacy authentication,” Slaboski says.

Boosting battery life without cramping style

Gen 3 improves continuous music playback time to six hours, versus the four hours offered by the previous generation of Echo Frames. It also bumps battery life to up to 14 hours of moderate usage spread across playback, talk time, notifications, and Alexa interactions.

Delivering the desired loudness, bass, and audio quality while optimizing for battery life was a careful balance.
Ravi Sanapala

The team couldn’t simply slap on a bigger battery without making the Echo Frames look less like normal glasses. And with sound quality high on the priority list as well, the devices were going to need as much juice as ever. The team focused on trimming power use in standby mode, ensuring that the overall battery consumption would go down without weakening the speakers when users needed them.

“Delivering the desired loudness, bass, and audio quality while optimizing for battery life was a careful balance,” says senior product manager Ravi Sanapala. “We need the battery to last throughout as much of the day as possible and for Alexa to be available whenever users need it.”

The architectural changes in speaker placement helped keep power needs low while improving audio. The team also tweaked the placement of the battery itself, distributing its capacity differently than in Gen 2. Sanapala adds that algorithmic changes were key in balancing idle-battery conservation and on-demand device usage.

“We had to collaborate with all of our cross-functional teams to optimize everything,” Sanapala says.

Gen 3 also features an all-new charging stand, which is designed for compatibility with all frame shapes and keeps lenses upright, protecting them from scratches while wirelessly charging.

Making smart eyewear look like eyewear

Making glasses that are suitable for everyday wear has always been a priority. “One of our goals has always been to develop technology that appears when you need it and disappears when you don’t,” says Wang.

Previous models of Echo Frames have come in a single, one-size-fits-all style.

A person is seen wearing Echo Frames sunglasses outside. The person carries a notebook and is looking down at it, and there are some buildings and blue sky in the background.
The Echo Frames team consulted with both internal and external eyewear designers to review common and popular styles of frames, and to survey potential customers about their preferences.

“That was a very intentional move,” Wang explains. “We wanted to start simply and learn from customer feedback.”

Gen 2’s flexible spring hinge and adjustable temple tips ensured that the single size fit many different faces. In fact, Wang says, while the goal was to fit around half of all potential users, they’ve found that 85 percent of the adult population can comfortably wear the Gen 2 design.

But with Gen 3, Wang says, the team needed to go beyond designing glasses that looked typical. Customers wanted glasses that looked stylish, too.

The team consulted with both internal and external eyewear designers to review common and popular styles of frames, as well as “edgier” designs, and to survey potential customers about their preferences. After testing options with beta customers, they settled on a variety of styles in various colors that cover a range of aesthetics. They also switched to an acetate material to match the feel of high-end eyewear.

Related content
How a team of designers, scientists, developers, and engineers worked together to create a truly unique device in Echo Show 10.

While each style will still come in a single size, the range of designs will accommodate even more faces than Gen 2, as the collection spans narrow, medium, and wide fits. Each style features adjustable temple tips constructed out of silicone around a lightweight titanium core for better fit. And despite the boost in battery life, the temples of Gen 3 frames have actually been slimmed down. Wang notes that competitive products often place large batteries behind a user’s ears. But presenting Echo Frames users with something that bulky and uncomfortable was never on the table.

“We were working with really heavy constraints,” Wang says. “So we have been very deliberate in making design choices in the service of our customer. That’s challenged us to be innovative and really push the limits of what’s possible in the architecture of our designs.”

Related content

US, CA, Sunnyvale
The Artificial General Intelligence (AGI) team is looking for a passionate, talented, and inventive Applied Scientist with a strong deep learning background, to help build industry-leading technology with generative AI (GenAI) and multi-modal systems. Key job responsibilities As an Applied Scientist with the AGI team, you will work with talented peers to develop algorithms and modeling techniques to advance the state of the art with multi-modal systems. Your work will directly impact our customers in the form of products and services that make use of vision and language technology. You will leverage Amazon’s large-scale computing resources to accelerate development with multi-modal Large Language Models (LLMs) and GenAI in Computer Vision. About the team The AGI team has a mission to push the envelope with multimodal LLMs and GenAI in Computer Vision, in order to provide the best-possible experience for our customers.
US, CA, San Francisco
Do you want to create intelligent, adaptable robots with global impact? We are seeking an experienced Applied Science Manager to lead a team of talented applied scientists and software engineers developing and deploying advanced manipulation strategies and algorithms. You will drive innovation that enables manipulation in high-contact, high-density, and diverse conditions with the speed and reliability that will delight our customers. Collaborating with cross-functional teams across hardware, software, and science, you will deliver reliable and high-performing solutions that will scale across geographies, applications, and conditions. You should enjoy the process of solving real-world problems that, quite frankly, haven’t been solved at scale anywhere before. Along the way, we guarantee you’ll get opportunities to be a disruptor, prolific innovator, and a reputed problem solver—someone who truly enables robotics to significantly impact the lives of millions of consumers. A day in the life - Prioritize being a great people manager: motivating, rewarding, and coaching your diverse team is the most important part of this role. You will recruit and retain top talent and excel in people and performance management tasks. - Set a vision for the team and create the technical roadmap that deliver results for customers while thinking big for future applications. - Guide the research, design, deployment, and evaluation of complex motion planning and control algorithms for contact-rich, cluttered, real-world manipulation problems. - Work closely with perception, hardware, and software teams to create integrated robotic solutions that are better than the sum of their parts. - Implement best practices in applied research and software development, managing project timelines, resources, and deliverables effectively. Amazon offers a full range of benefits for 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 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!
US, WA, Seattle
Amazon Economics is seeking Structural Economist (STRUC) Interns who are passionate about applying structural econometric methods to solve real-world business challenges. STRUC economists specialize in the econometric analysis of models that involve the estimation of fundamental preferences and strategic effects. In this full-time internship (40 hours per week, with hourly compensation), you'll work with large-scale datasets to model strategic decision-making and inform business optimization, gaining hands-on experience that's directly applicable to dissertation writing and future career placement. Key job responsibilities As a STRUC Economist Intern, you'll specialize in structural econometric analysis to estimate fundamental preferences and strategic effects in complex business environments. Your responsibilities include: - Analyze large-scale datasets using structural econometric techniques to solve complex business challenges - Applying discrete choice models and methods, including logistic regression family models (such as BLP, nested logit) and models with alternative distributional assumptions - Utilizing advanced structural methods including dynamic models of customer or firm decisions over time, applied game theory (entry and exit of firms), auction models, and labor market models - Building datasets and performing data analysis at scale - Collaborating with economists, scientists, and business leaders to develop data-driven insights and strategic recommendations - Tackling diverse challenges including pricing analysis, competition modeling, strategic behavior estimation, contract design, and marketing strategy optimization - Helping business partners formalize and estimate business objectives to drive optimal decision-making and customer value - Build and refine comprehensive datasets for in-depth structural economic analysis - Present complex analytical findings to business leaders and stakeholders
US, WA, Seattle
Amazon Economics is seeking Reduced Form Causal Analysis (RFCA) Economist Interns who are passionate about applying econometric methods to solve real-world business challenges. RFCA represents the largest group of economists at Amazon, and these core econometric methods are fundamental to economic analysis across the company. In this full-time internship (40 hours per week, with hourly compensation), you'll work with large-scale datasets to analyze causal relationships and inform strategic business decisions, gaining hands-on experience that's directly applicable to dissertation writing and future career placement. Key job responsibilities As an RFCA Economist Intern, you'll specialize in econometric analysis to determine causal relationships in complex business environments. Your responsibilities include: - Analyze large-scale datasets using advanced econometric techniques to solve complex business challenges - Applying econometric techniques such as regression analysis, binary variable models, cross-section and panel data analysis, instrumental variables, and treatment effects estimation - Utilizing advanced methods including differences-in-differences, propensity score matching, synthetic controls, and experimental design - Building datasets and performing data analysis at scale - Collaborating with economists, scientists, and business leaders to develop data-driven insights and strategic recommendations - Tackling diverse challenges including program evaluation, elasticity estimation, customer behavior analysis, and predictive modeling that accounts for seasonality and time trends - Build and refine comprehensive datasets for in-depth economic analysis - Present complex analytical findings to business leaders and stakeholders
US, WA, Seattle
Amazon Economics is seeking Forecasting, Macroeconomics and Finance (FMF) Economist Interns who are passionate about applying time-series econometric methods to solve real-world business challenges. FMF economists interpret and forecast Amazon business dynamics by combining advanced time-series statistical methods with strong economic analysis and intuition. In this full-time internship (40 hours per week, with hourly compensation), you'll work with large-scale datasets to forecast business trends and inform strategic decisions, gaining hands-on experience that's directly applicable to dissertation writing and future career placement. Key job responsibilities As an FMF Economist Intern, you'll specialize in time-series econometric analysis to understand, predict, and optimize Amazon's business dynamics. Your responsibilities include: - Analyze large-scale datasets using advanced time-series econometric techniques to solve complex business challenges - Applying frontier methods in time series econometrics, including forecasting models, dynamic systems analysis, and econometric models that combine macro and micro data - Developing formal models to understand past and present business dynamics, predict future trends, and identify relevant risks and opportunities - Building datasets and performing data analysis at scale using world-class data tools - Collaborating with economists, scientists, and business leaders to develop data-driven insights and strategic recommendations - Tackling diverse challenges including analyzing drivers of growth and profitability, forecasting business metrics, understanding how customer experience interacts with external conditions, and evaluating short, medium, and long-term business dynamics - Build and refine comprehensive datasets for in-depth time-series economic analysis - Present complex analytical findings to business leaders and stakeholders
US, WA, Seattle
Do you want a role with deep meaning and the ability to have a global impact? Hiring top talent is not only critical to Amazon’s success – it can literally change the world. It took a lot of great hires to deliver innovations like AWS, Prime, and Alexa, which make life better for millions of customers around the world. As part of the Intelligent Talent Acquisition (ITA) team, you'll have the opportunity to reinvent Amazon’s hiring process with unprecedented scale, sophistication, and accuracy. ITA is an industry-leading people science and technology organization made up of scientists, engineers, analysts, product professionals, and more. Our shared goal is to fairly and precisely connect the right people to the right jobs. Last year, we delivered over 6 million online candidate assessments, driving a merit-based hiring approach that gives candidates the opportunity to showcase their true skills. Each year we also help Amazon deliver billions of packages around the world by making it possible to hire hundreds of thousands of associates in the right quantity, at the right location, at exactly the right time. You’ll work on state-of-the-art research with advanced software tools, new AI systems, and machine learning algorithms to solve complex hiring challenges. Join ITA in using cutting-edge 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. Within ITA, the Global Hiring Science (GHS) team designs and implements innovative hiring solutions at scale. We work in a fast-paced, global environment where we use research to solve complex problems and build scalable hiring products that deliver measurable impact to our customers. We are seeking selection researchers with a strong foundation in hiring assessment development, legally-defensible validation approaches, research and experimental design, and data analysis. Preferred candidates will have experience across the full hiring assessment lifecycle, from solution design to content development and validation to impact analysis. We are looking for equal parts researcher and consultant, who is able to influence customers with insights derived from science and data. You will work closely with cross-functional teams to design new hiring solutions and experiment with measurement methods intended to precisely define exactly what job success looks like and how best to predict it. Key job responsibilities What you’ll do as a GHS Research Scientist: • Design large-scale personnel selection research that shapes Amazon’s global talent assessment practices across a variety of topics (e.g., assessment validation, measuring post-hire impact) • Partner with key stakeholders to create innovative solutions that blend scientific rigor with real-world business impact while navigating complex legal and professional standards • Apply advanced statistical techniques to analyze massive, diverse datasets to uncover insights that optimize our candidate evaluation processes and drive hiring excellence • Explore emerging technologies and innovative methodologies to enhance talent measurement while maintaining Amazon's commitment to scientific integrity • Translate complex research findings into compelling, actionable strategies that influence senior leader/business decisions and shape Amazon's talent acquisition roadmap • Write impactful documents that distill intricate scientific concepts into clear, persuasive communications for diverse audiences, from data scientists to business leaders • Ensure effective teamwork, communication, collaboration, and commitment across multiple teams with competing priorities A day in the life Imagine diving into challenges that impact millions of employees across Amazon's global operations. As a GHS Research Scientist, you'll tackle questions about hiring and organizational effectiveness on a global scale. Your day might begin with analyzing datasets to inform how we attract and select world-class talent. Throughout the day, you'll collaborate with peers in our research community, discussing different research methodologies and sharing innovative approaches to solving unique personnel challenges. This role offers a blend of focused analytical time and interacting with stakeholders across the globe.
CA, BC, Vancouver
The Alexa Daily Essentials team delivers experiences critical to how customers interact with Alexa as part of daily life. Alexa users engage with our products across experiences connected to Timers, Alarms, Calendars, Food, and News. Our experiences include critical time saving techniques, ad-supported news audio and video, and in-depth kitchen guidance aimed at serving the needs of the family from sunset to sundown. As a Data Scientist on our team, you'll work with complex data, develop statistical methodologies, and provide critical product insights that shape how we build and optimize our solutions. You will work closely with your Analytics and Applied Science teammates. You will build frameworks and mechanisms to scale data solutions across our organization. If you are passionate about redefining how AI can improves everyone's daily life, we’d love to hear from you. Key job responsibilities Problem-Solving - Analyze complex data (including healthcare data, experimental data, and large-scale datasets) to identify patterns, inform product decisions, and understand root causes of anomalies. - Develop analysis and modeling approaches to drive product and engineering actions to identify patterns, insights, and understand root causes of anomalies. Your solutions directly improve the customer experience. - Independently work with product partners to identify problems and opportunities. Apply a range of data science techniques and tools to solve these problems. Use data driven insights to inform product development. Work with cross-disciplinary teams to mechanize your solution into scalable and automated frameworks. Data Infrastructure - Build data pipelines, and identify novel data sources to leverage in analytical work - both from within Alexa and from cross Amazon - Acquire data by building the necessary SQL / ETL queries Communication - Excel at communicating complex ideas to technical and non-technical audiences. - Build relationships with stakeholders and counterparts. Work with stakeholders to translate causal insights into actionable recommendations - Force multiply the work of the team with data visualizations, presentations, and/or dashboards to drive awareness and adoption of data assets and product insights - Collaborate with cross-functional teams. Mentor teammates to foster a culture of continuous learning and development
US, WA, Seattle
The Automated Reasoning Group in the AWS Neuron Compiler team is looking for an Applied Scientist to work on the intersection of Artificial Intelligence and program analysis to raise the code quality bar in our state-of-the-art deep learning compiler stack. This stack is designed to optimize application models across diverse domains, including Large Language and Vision, originating from leading frameworks such as PyTorch, TensorFlow, and JAX. Your role will involve working closely with our custom-built Machine Learning accelerators, Inferentia and Trainium, which represent the forefront of AWS innovation for advanced ML capabilities, and is the underpinning of Generative AI. In this role as an Applied Scientist, you'll be instrumental in designing, developing, and deploying analyzers for ML compiler stages and compiler IRs. You will architect and implement business-critical tooling, publish cutting-edge research, and mentor a brilliant team of experienced scientists and engineers. You will need to be technically capable, credible, and curious in your own right as a trusted AWS Neuron engineer, innovating on behalf of our customers. Your responsibilities will involve tackling crucial challenges alongside a talented engineering team, contributing to leading-edge design and research in compiler technology and deep-learning systems software. Strong experience in programming languages, compilers, program analyzers, and program synthesis engines will be a benefit in this role. A background in machine learning and AI accelerators is preferred but not required. A day in the life 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. 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. 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, NY, New York
The Sponsored Products and Brands (SPB) team at Amazon Ads is re-imagining the advertising landscape through state-of-the-art generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights. We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising. The Off-Search team within Sponsored Products and Brands (SPB) is focused on building delightful ad experiences across various surfaces beyond Search on Amazon—such as product detail pages, the homepage, and store-in-store pages—to drive monetization. Our vision is to deliver highly personalized, context-aware advertising that adapts to individual shopper preferences, scales across diverse page types, remains relevant to seasonal and event-driven moments, and integrates seamlessly with organic recommendations such as new arrivals, basket-building content, and fast-delivery options. To execute this vision, we work in close partnership with Amazon Stores stakeholders to lead the expansion and growth of advertising across Amazon-owned and -operated pages beyond Search. We operate full stack—from backend ads-retail edge services, ads retrieval, and ad auctions to shopper-facing experiences—all designed to deliver meaningful value. Curious about our advertising solutions? Discover more about Sponsored Products and Sponsored Brands to see how we’re helping businesses grow on Amazon.com and beyond! Key job responsibilities This role will be pivotal in redesigning how ads contribute to a personalized, relevant, and inspirational shopping experience, with the customer value proposition at the forefront. Key responsibilities include, but are not limited to: - Contribute to the design and development of GenAI, deep learning, multi-objective optimization and/or reinforcement learning empowered solutions to transform ad retrieval, auctions, whole-page relevance, and/or bespoke shopping experiences. - Collaborate cross-functionally with other scientists, engineers, and product managers to bring scalable, production-ready science solutions to life. - Stay abreast of industry trends in GenAI, LLMs, and related disciplines, bringing fresh and innovative concepts, ideas, and prototypes to the organization. - Contribute to the enhancement of team’s scientific and technical rigor by identifying and implementing best-in-class algorithms, methodologies, and infrastructure that enable rapid experimentation and scaling. - Mentor and grow junior scientists and engineers, cultivating a high-performing, collaborative, and intellectually curious team. A day in the life As an Applied Scientist on the Sponsored Products and Brands Off-Search team, you will contribute to the development in Generative AI (GenAI) and Large Language Models (LLMs) to revolutionize our advertising flow, backend optimization, and frontend shopping experiences. This is a rare opportunity to redefine how ads are retrieved, allocated, and/or experienced—elevating them into personalized, contextually aware, and inspiring components of the customer journey. You will have the opportunity to fundamentally transform areas such as ad retrieval, ad allocation, whole-page relevance, and differentiated recommendations through the lens of GenAI. By building novel generative models grounded in both Amazon’s rich data and the world’s collective knowledge, your work will shape how customers engage with ads, discover products, and make purchasing decisions. If you are passionate about applying frontier AI to real-world problems with massive scale and impact, this is your opportunity to define the next chapter of advertising science. About the team The Off-Search team within Sponsored Products and Brands (SPB) is focused on building delightful ad experiences across various surfaces beyond Search on Amazon—such as product detail pages, the homepage, and store-in-store pages—to drive monetization. Our vision is to deliver highly personalized, context-aware advertising that adapts to individual shopper preferences, scales across diverse page types, remains relevant to seasonal and event-driven moments, and integrates seamlessly with organic recommendations such as new arrivals, basket-building content, and fast-delivery options. To execute this vision, we work in close partnership with Amazon Stores stakeholders to lead the expansion and growth of advertising across Amazon-owned and -operated pages beyond Search. We operate full stack—from backend ads-retail edge services, ads retrieval, and ad auctions to shopper-facing experiences—all designed to deliver meaningful value. Curious about our advertising solutions? Discover more about Sponsored Products and Sponsored Brands to see how we’re helping businesses grow on Amazon.com and beyond!
US, MD, Jessup
Application deadline: Applications will be accepted on an ongoing basis Are you excited to help the US Intelligence Community design, build, and implement AI algorithms, including advanced Generative AI solutions, to augment decision making while meeting the highest standards for reliability, transparency, and scalability? The Amazon Web Services (AWS) US Federal Professional Services team works directly with US Intelligence Community agencies and other public sector entities to achieve their mission goals through the adoption of Machine Learning (ML) and Generative AI methods. We build models for text, image, video, audio, and multi-modal use cases, leveraging both traditional ML approaches and state-of-the-art generative models including Large Language Models (LLMs), text-to-image generation, and other advanced AI capabilities to fit the mission. Our team collaborates across the entire AWS organization to bring access to product and service teams, to get the right solution delivered and drive feature innovation based on customer needs. At AWS, we're hiring experienced data scientists with a background in both traditional and generative AI who can help our customers understand the opportunities their data presents, and build solutions that earn the customer trust needed for deployment to production systems. In this role, you will work closely with customers to deeply understand their data challenges and requirements, and design tailored solutions that best fit their use cases. You should have broad experience building models using all kinds of data sources, and building data-intensive applications at scale. You should possess excellent business acumen and communication skills to collaborate effectively with stakeholders, develop key business questions, and translate requirements into actionable solutions. You will provide guidance and support to other engineers, sharing industry best practices and driving innovation in the field of data science and AI. This position requires that the candidate selected must currently possess and maintain an active TS/SCI Security Clearance. The position further requires the candidate to opt into a commensurate clearance for each government agency for which they perform AWS work. Key job responsibilities As a Data Scientist, you will: - Collaborate with AI/ML scientists and architects to research, design, develop, and evaluate AI algorithms to address real-world challenges - Interact with customers directly to understand the business problem, help and aid them in implementation of 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 - This position may require up to 25% local travel. About the team 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. 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. 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 (diversity) conferences, inspire us to never stop embracing our uniqueness. 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 flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. 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.