In the second-generation Echo Buds, Amazon engineers were able to produce a device that is 21 percent smaller than the first version, while maintaining costs, through a multitude of innovations and integration of components.

How the second-gen Echo Buds got smaller and better

Take a behind-the-scenes look at the unique challenges the engineering teams faced, and how they used scientific research to drive fundamental innovation.

Notebook computers, tablets, and smartphones get the tech headlines, but these are largely mature products at this point. Smaller, more personal devices are going through a torrent of iteration and innovation.

Bluetooth wireless headphones are a highly competitive category, with products with bare-bones features available for less than $50, and feature-packed devices available at prices ranging all the way up to $400.

The first Amazon Echo Buds appeared in 2019, and, the follow-up second-gen Echo Buds in April 2021. The team at Amazon improved the second-gen earbuds in almost every way. This is a behind-the-scenes look at the unique challenges the engineering teams faced in creating the latest generation Echo Buds, and how they used scientific research to drive fundamental innovation to overcome those challenges.

Ultimately, Amazon’s team was able to a deliver feature-rich product that competes with products at the high end of the price range for $120.

Atif Noori was the principal product manager for both generations of Echo Buds. Reflecting Amazon’s customer focus, he said the process of designing the latest Echo Buds began with understanding the desires of the customer.

“We work backwards from the customers and build out a set of product requirements. From there we work across multiple talented teams to deliver a lovable product,” he said.

What customers want is great audio, a comfortable fit, long battery life, and excellent connectivity with their smartphones. Of course, many of these are in tension with one another. At the high end of the hearables category, customers also want advanced features like noise cancellation and cloud-based voice services like Alexa.

Echo Buds, Glacier White, Outside.jpg
For the second-generation Echo Buds, engineers worked to redesign the main Bluetooth chip and the audio co-processor in such a way that those two components could perform the tasks of five different components in the first-generation device.

Given this catalog of customer expectations, the nugget-sized wireless earbuds are giants of engineering challenges.

Reducing size to improve comfort and fit, while still maintaining connectivity performance, staying under comfortable temperatures limits, and meeting the customer’s battery life expectations with more features, was a challenge, but one the engineering team said they were excited to tackle.   

Milos Jorgovanovic, principal system architect at Amazon Lab 126, says size and cost are the constant constraints. The Amazon engineers were able to produce a device that is 21 percent smaller than the first version Echo Buds, while maintaining costs, through a multitude of innovations and integration of components.

This began with the processors, or, to use the engineers’ lingo, the silicon, which are the heart of the device. To make the device smaller, the engineers needed to reduce the size of the battery. Easily enough done on its own, except the team also needed to do this without reducing the device's battery life.

"And really for that, the key piece is the power consumption of the silicon platform itself," Jorgovanovic said. "At the same time, we are basically trying to offer high-end features at a much lower power consumption and lower cost."

For the second-generation Echo Buds, team worked with manufacturers to redesign the main Bluetooth chip and the audio co-processor in such a way that those two components could perform the tasks of five different components found in the first-generation device.

"We basically cut the power consumption for audio and Alexa processing by at least a factor of two from what it was before," Jorgovanovic said.

We basically cut the power consumption for audio and Alexa processing by at least a factor of two from what it was before.
Milos Jorgovanovic

This was done while simultaneously improving the Alexa’s ability to hear customers speak.

Amazon started the voice category with the original Echo and Alexa launch in November 2014, so it makes sense that the latest Echo Buds would offer seamless Alexa functionality. With Alexa, a user can not only play music and make phone calls, but also set reminders, request information, and in certain cities, plan public transportation routes and get information on the train or bus they're hoping to catch, all while leaving their phone in their pocket.

"If a customer wants to take Alexa on the go, they can do that and have the same experience as they do with an Echo in their home," Noori said. "It's even more than that though. The responses are tailored for when you're on the go. For example, you can ask Alexa to remind you to buy tahini when you arrive at Whole Foods. And in some stores, you can then ask Alexa if tahini is in stock, or ask which aisle the tahini is on, which is pretty awesome.”

Achieving all of that requires not only integration with the cloud, but also a good bit of on-device processing. Jorgovanovic said improvements in the new processor allowed this to be done with less power consumption.

"We put a better digital signal processor in there, but the second, and more important piece, is that this chip was designed so that it allows very aggressive frequency and voltage scaling," he said. "What it means is that if the device is basically sitting in the air, doing very little processing, we are able to lower both the frequency and the voltage on that chip and have the chip consume much less energy."

If the user speaks and, for example, asks a friend, "Hey, Jason, how are you doing?" the device will run a small amount of processing to determine if the user said "Alexa." If the user did say "Alexa," the digital signal processor (DSP) is boosted even further, increasing the voltage, boosting the frequency, and engaging in more complex compute. At that point the device is processing the Alexa event — the information is sent to the cloud and then the response is played when it is received.

"We basically have these levels of processing, and we set the frequency and the voltage on the processor to the adequate level for the amount of processing we need. This is one of the two main things that we've done in gen two to scale down the power consumption,” Jorgovanovic explained. “The second big thing was integrating more functionality into the main Bluetooth SoC [system on a chip] by innovating on the Bluetooth protocol between the two earbuds, which reduced the number of components and power spent on interconnect. Overall, we reduced total device power by more than 35 percent relative to the first Echo Buds, and specific to that DSP processing for audio and Alexa, by at least a factor of two, if not more. And that's just, wow."

Reducing the power of the processors brought another benefit: reduced heat. "Because we pack in so much, we have to factor in heat dissipation," Noori said.  "It was not like you can add on cooling fins or a big heat sink. It required careful simulation and design."

Beyond the silicon, another major constraint in size and cost are the antennas.

Connectivity is a hurdle in wireless Bluetooth headphones because they are partially hidden in the ear. And while ears can block frequencies, the human body is also effective at blocking signals. The user's smartphone needs to connect with one of the earbuds, and then the two earbuds need to send packets to each other, with as little latency as possible.

"That's really important — the synchronization of the two ear buds — because our hearing is very sensitive to this," Jorgovanovic said. "Something like a hundred microseconds of delta between left and right can easily be felt. And, the effect is the user will sense that the audio is not coming from straight ahead, but instead coming from one side or the other."

Balamurugan Shanmugam, senior antenna design engineer, says the connectivity issues are a challenge for all wearable devices.

"This is an inherent physics problem, right? I mean, this is not unique to Amazon. Anyone working on body-worn devices or even looking just at medical devices such as wireless-enabled pacemakers will encounter the same problem," he said.

Shanmugam's challenge was to improve connectivity in a smaller package. His team's first go at the problem developed a solution, but the manufacturing costs were too high. It was time to develop a novel solution.

Just as the engineers were able to reduce the number of processors in the device, they also were able to integrate functions to accommodate a new antenna. The best location for the antenna is in the front center of the device, but that is also where a user expects to tap or use gestures. On the first-generation Echo Bud, the touch sensor and electrostatic discharge (ESD) circuits were utilizing the location an antenna needs to maximize wireless performance. To address that, the engineers invented an integrated antenna design that combines the antenna, touch, and ESD subsystems.

"The newest Echo Bud has integrated antenna, touch, and electrostatic discharge to optimize wireless performance," Shanmugam said.

Noori said that connectivity is among the features that stand out in the latest Echo Buds. "Connectivity is very solid on these devices; I'm definitely proud of the connectivity performance. I think we nailed that."

And there’s more to come.

"I think there's a lot of interesting things that can be done with earbuds that are outside of basic music playback," Noori said. "We’re continuing to innovate on behalf of our customers, and pushing out software updates. Echo Buds will continue to get better and smarter over time."

Get them in black or white with a wired charing case for $119.99 or with a wireless charging case for $139.99.

Related content

US, WA, Seattle
The Amazon Economics Team is hiring Economist Interns. We are looking for detail-oriented, organized, and responsible individuals who are eager to learn how to work with large and complicated data sets to solve real-world business problems. Some knowledge of econometrics, as well as basic familiarity with Stata, R, or Python is necessary. Experience with SQL, UNIX, Sawtooth, and Spark would be a plus. These are full-time positions at 40 hours per week, with compensation being awarded on an hourly basis. You will learn how to build data sets and perform applied econometric analysis at Internet speed collaborating with economists, data scientists and MBAʼs. These skills will translate well into writing applied chapters in your dissertation and provide you with work experience that may help you with future job market placement. Roughly 85% of interns from previous cohorts have converted to full-time economics employment at Amazon. If you are interested, please send your CV to our mailing list at We are open to hiring candidates to work out of one of the following locations: Seattle, WA, USA
GB, Cambridge
Our team undertakes research together with multiple organizations to advance the state-of-the-art in speech technologies. We not only work on giving Alexa, the ground-breaking service that powers Echo, her voice, but we also develop cutting-edge technologies with Amazon Studios, the provider of original content for Prime Video. Do you want to be part of the team developing the latest technology that impacts the customer experience of ground-breaking products? Then come join us and make history. We are looking for a passionate, talented, and inventive Senior Applied Scientist with a background in Machine Learning to help build industry-leading Speech, Language and Video technology. As a Senior Applied Scientist at Amazon you will work with talented peers to develop novel algorithms and modelling techniques to drive the state of the art in speech and vocal arts synthesis. Position Responsibilities: - Participate in the design, development, evaluation, deployment and updating of data-driven models for digital vocal arts applications. - Participate in research activities including the application and evaluation and digital vocal and video arts techniques for novel applications. - Research and implement novel ML and statistical approaches to add value to the business. - Mentor junior engineers and scientists. We are open to hiring candidates to work out of one of the following locations: Cambridge, GBR
US, VA, Arlington
The People eXperience and Technology Central Science Team (PXTCS) uses economics, behavioral science, statistics, and machine learning to proactively identify mechanisms and process improvements which simultaneously improve Amazon and the lives, wellbeing, and the value of work to Amazonians. We are an interdisciplinary team that combines the talents of science and engineering to develop and deliver solutions that measurably achieve this goal. We are looking for economists who are able to apply economic methods to address business problems. The ideal candidate will work with engineers and computer scientists to estimate models and algorithms on large scale data, design pilots and measure their impact, and transform successful prototypes into improved policies and programs at scale. We are looking for creative thinkers who can combine a strong technical economic toolbox with a desire to learn from other disciplines, and who know how to execute and deliver on big ideas as part of an interdisciplinary technical team. Ideal candidates will work in a team setting with individuals from diverse disciplines and backgrounds. They will work with teammates to develop scientific models and conduct the data analysis, modeling, and experimentation that is necessary for estimating and validating models. They will work closely with engineering teams to develop scalable data resources to support rapid insights, and take successful models and findings into production as new products and services. They will be customer-centric and will communicate scientific approaches and findings to business leaders, listening to and incorporate their feedback, and delivering successful scientific solutions. Key job responsibilities Use reduced-form causal analysis and/or structural economic modeling methods to evaluate the impact of policies on employee outcomes, and examine how external labor market and economic conditions impact Amazon's ability to hire and retain talent. A day in the life Work with teammates to apply economic methods to business problems. This might include identifying the appropriate research questions, writing code to implement a DID analysis or estimate a structural model, or writing and presenting a document with findings to business leaders. Our economists also collaborate with partner teams throughout the process, from understanding their challenges, to developing a research agenda that will address those challenges, to help them implement solutions. About the team We are a multidisciplinary team that combines the talents of science and engineering to develop innovative solutions to make Amazon Earth's Best Employer. We are open to hiring candidates to work out of one of the following locations: Arlington, VA, USA
US, WA, Seattle
We are expanding our Global Risk Management & Claims team and insurance program support for Amazon’s growing risk portfolio. This role will partner with our risk managers to develop pricing models, determine rate adequacy, build underwriting and claims dashboards, estimate reserves, and provide other analytical support for financially prudent decision making. As a member of the Global Risk Management team, this role will provide actuarial support for Amazon’s worldwide operation. Key job responsibilities ● Collaborate with risk management and claims team to identify insurance gaps, propose solutions, and measure impacts insurance brings to the business ● Develop pricing mechanisms for new and existing insurance programs utilizing actuarial skills and training in innovative ways ● Build actuarial forecasts and analyses for businesses under rapid growth, including trend studies, loss distribution analysis, ILF development, and industry benchmarks ● Design actual vs expected and other metrics dashboards to assist decision makings in pricing analysis ● Create processes to monitor loss cost and trends ● Propose and implement loss prevention initiatives with impact on insurance pricing in mind ● Advise underwriting decisions with analysis on driver risk profile ● Support insurance cost budgeting activities ● Collaborate with external vendors and other internal analytics teams to extract insurance insight ● Conduct other ad hoc pricing analyses and risk modeling as needed We are open to hiring candidates to work out of one of the following locations: Arlington, VA, USA | New York, NY, USA | Seattle, WA, USA
US, NY, New York
The Amazon SCOT Forecasting team seeks a Senior Applied Scientist to join our team. Our research team conducts research into the theory and application of reinforcement learning. This research is shared in top journals and conferences and has a significant impact on the field. Through our launch of several Deep RL models into production, our work also affects decision making in the real world. Members of our group have varied interests—from the mathematical foundations of reinforcement learning, to language modeling, to maintaining the performance of generative models in the face of copyrights, and more. Recent work has focused on sample efficiency of RL algorithms, treatment effect estimation, and RL agents integrating real-world constraints, as applied in supply chains. Previous publications include: - Linear Reinforcement Learning with Ball Structure Action Space - Meta-Analysis of Randomized Experiments with Applications to Heavy-Tailed Response Data - A Few Expert Queries Suffices for Sample-Efficient RL with Resets and Linear Value Approximation - Deep Inventory Management - What are the Statistical Limits of Offline RL with Linear Function Approximation? Working collaboratively with a group of fellow scientists and engineers, you will identify complex problems and develop solutions in the RL space. We encourage collaboration across teammates and their areas of specialty, leading to creative and ambitious projects with the goal of publication and production. Key job responsibilities - Drive collaborative research and creative problem solving - Constructively critique peer research; mentor junior scientists - Create experiments and prototype implementations of new algorithms and techniques - Collaborate with engineering teams to design and implement software built on these new algorithms - Contribute to progress of the Amazon and broader research communities by producing publications We are open to hiring candidates to work out of one of the following locations: New York, NY, USA
US, CA, Virtual Location - California
If you are interested in this position, please apply on Twitch's Career site About Us: Launched in 2011, Twitch is a global community that comes together each day to create multiplayer entertainment: unique, live, unpredictable experiences created by the interactions of millions. We bring the joy of co-op to everything, from casual gaming to world-class esports to anime marathons, music, and art streams. Twitch also hosts TwitchCon, where we bring everyone together to celebrate and grow their personal interests and passions. We're always live at Twitch. About the Role: As a Data Scientist, Analytics member of the Data Platform - Insights team, you'll provide data analysis and support for platform, service, and operational engineering teams at Twitch, shaping the way success is measured. Defining what questions should be asked and scaling analytics methods and tools to support our growing business. Additionally, you will help support the vision for business analytics, solutions architecture for data related business constructs, as well as tactical execution such as experiment analysis and campaign performance reporting. You are paving the way for high-quality, high-velocity decisions and will report to the Manager, Data Science. For this role, we're looking for an experienced data staff who will oversee data instrumentation, dashboard/report building, metrics reviews, inform team investments, guidance on success/failure metrics and ad-hoc analysis. You will also work with technical and non-technical staff members throughout the company, and your effort will have an impact on hundreds of partners at Twitch You Will: - Work with members of Platforms & Services to guide them towards better decision making from the available data. - Promote data knowledge and insights through managing communications with partners and other teams, collaborate with colleagues to complete data projects and ensure all parties can use the insights to further improve. - Maintain a customer-centric focus while being a domain and product expert through data, develop trust amongst peers, and ensure that the teams and programs have access to data to make decisions - Manage ambiguous problems and adapt tools to answer complicated questions. - Identify the trade-offs between speed and quality of different approaches. - Create analytical frameworks to measure team success by partnering with teams to establish success metrics, create approaches to track the data and troubleshoot errors, measure and evaluate the data to develop a common language for all colleagues to understand these metrics. - Operationalize data processes to provide partners with ad-hoc analysis, automated dashboards, and self-service reporting tools so that everyone gets a good sense of the state of the business Perks: - Medical, Dental, Vision & Disability Insurance - 401(k), Maternity & Parental Leave - Flexible PTO - Commuter Benefits - Amazon Employee Discount - Monthly Contribution & Discounts for Wellness Related Activities & Programs (e.g., gym memberships, off-site massages), -Breakfast, Lunch & Dinner Served Daily - Free Snacks & Beverages We are open to hiring candidates to work out of one of the following locations: Irvine, CA, USA | Seattle, WA, USA | Virtual Location - CA
US, WA, Bellevue
Have you ever ordered a product on Amazon and when that box with the smile arrived you wondered how it got to you so fast? Have you wondered where it came from and how much it cost Amazon to deliver it to you? Have you also wondered what are different ways that the transportation assets can be used to delight the customer even more. If so, the Amazon transportation Services, Product and Science is for you . We manage the delivery of tens of millions of products every week to Amazon’s customers, achieving on-time delivery in a cost-effective manner. We are looking for an enthusiastic, customer obsessed Applied Scientist with strong scientific thinking, good software and statistics experience, skills to help manage projects and operations, improve metrics, and develop scalable processes and tools. The primary role of an Applied Scientist within Amazon is to address business challenges through building a compelling case, and using data to influence change across the organization. This individual will be given responsibility on their first day to own those business challenges and the autonomy to think strategically and make data driven decisions. Decisions and tools made in this role will have significant impact to the customer experience, as it will have a major impact on how we operate the middle mile network. Ideal candidates will be a high potential, strategic and analytic graduate with a PhD in (Operations Research, Statistics, Engineering, and Supply Chain) ready for challenging opportunities in the core of our world class operations space. Great candidates have a history of operations research, machine learning , and the ability to use data and research to make changes. This role requires robust skills in research and implementation of scalable products and models . This individual will need to be able to work with a team, but also be comfortable making decisions independently, in what is often times an ambiguous environment. Responsibilities may include: - Develop input and assumptions based preexisting models to estimate the costs and savings opportunities associated with varying levels of network growth and operations - Creating metrics to measure business performance, identify root causes and trends, and prescribe action plans - Managing multiple projects simultaneously - Working with technology teams and product managers to develop new tools and systems to support the growth of the business - Communicating with and supporting various internal stakeholders and external audiences We are open to hiring candidates to work out of one of the following locations: Bellevue, WA, USA
US, CA, Los Angeles
The Alexa team is looking for a passionate, talented, and inventive Applied Scientist with a strong machine learning background, to help build industry-leading Speech and Language technology. Key job responsibilities As an Applied Scientist with the Alexa team, you will work with talented peers to develop novel algorithms and modeling techniques to advance the state of the art in spoken language understanding. Your work will directly impact our customers in the form of products and services that make use of speech and language technology. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in spoken language understanding. About the team The Alexa team has a mission to push the envelope in Automatic Speech Recognition (ASR), Natural Language Understanding (NLU), and Audio Signal Processing, in order to provide the best-possible experience for our customers. We are open to hiring candidates to work out of one of the following locations: Los Angeles, CA, USA
US, WA, Seattle
Are you fascinated by the power of Natural Language Processing (NLP) and Large Language Models (LLM) to transform the way we interact with technology? Are you passionate about applying advanced machine learning techniques to solve complex challenges in the e-commerce space? If so, Amazon's International Seller Services team has an exciting opportunity for you as an Applied Scientist. At Amazon, we strive to be Earth's most customer-centric company, where customers can find and discover anything they want to buy online. Our International Seller Services team plays a pivotal role in expanding the reach of our marketplace to sellers worldwide, ensuring customers have access to a vast selection of products. As an Applied Scientist, you will join a talented and collaborative team that is dedicated to driving innovation and delivering exceptional experiences for our customers and sellers. You will be part of a global team that is focused on acquiring new merchants from around the world to sell on Amazon’s global marketplaces around the world. The position is based in Seattle but will interact with global leaders and teams in Europe, Japan, China, Australia, and other regions. Join us at the Central Science Team of Amazon's International Seller Services and become part of a global team that is redefining the future of e-commerce. With access to vast amounts of data, cutting-edge technology, and a diverse community of talented individuals, you will have the opportunity to make a meaningful impact on the way sellers engage with our platform and customers worldwide. Together, we will drive innovation, solve complex problems, and shape the future of e-commerce. Please visit for more information Key job responsibilities - Apply your expertise in LLM models to design, develop, and implement scalable machine learning solutions that address complex language-related challenges in the international seller services domain. - Collaborate with cross-functional teams, including software engineers, data scientists, and product managers, to define project requirements, establish success metrics, and deliver high-quality solutions. - Conduct thorough data analysis to gain insights, identify patterns, and drive actionable recommendations that enhance seller performance and customer experiences across various international marketplaces. - Continuously explore and evaluate state-of-the-art NLP techniques and methodologies to improve the accuracy and efficiency of language-related systems. - Communicate complex technical concepts effectively to both technical and non-technical stakeholders, providing clear explanations and guidance on proposed solutions and their potential impact. We are open to hiring candidates to work out of one of the following locations: Seattle, WA, USA
US, CA, Palo Alto
We’re working to improve shopping on Amazon using the conversational capabilities of large language models. We are open to hiring candidates to work out of one of the following locations: Palo Alto, CA, USA