NASA's Orion spacecraft shown splashing down in the Pacific Ocean, west of Baja California, at 9:40 a.m. PST Sunday, Dec. 11.
NASA's Orion spacecraft shown splashing down in the Pacific Ocean, west of Baja California, at 9:40 a.m. PST Sunday, Dec. 11.
NASA

The story behind how Amazon integrated Alexa into NASA’s Orion spacecraft

From physical constraints to acoustic challenges, learn how Amazon collaborated with NASA and Lockheed Martin to get Alexa to work in space.

In September 2018, Amazon’s principal solutions architect Philippe Lantin received a call from his manager.

“He said that there was something unique on the horizon, and that their team was being roped into a one-in-a-lifetime opportunity,” says Lantin.

This was no understatement: on the horizon was an opportunity for Amazon to collaborate with Lockheed Martin Space, and integrate Alexa into NASA’s Orion spacecraft. Orion is the first human-rated spacecraft to visit the moon in more than 40 years.

“NASA is trying to engage the public more as we enter this new era of space travel, where we are setting the stage for extra-planetary exploration,” says Lantin. “Given that over 100 million Alexa-enabled devices have already been sold, having Alexa answer questions like 'Alexa, how far to the moon?' and 'Alexa, how fast is Orion going?' is a great way to get people around the world involved in NASA’s missions.”

Setting up an Echo device on Earth is simple: all you need is a Wi-Fi connection and the Alexa app. However, things are far more complicated in space.

“We had several constraints we had to contend with,” says Lantin.
The Alexa team had to operate within a key physical constraint: the shape of the device. The contours of a smart speaker greatly influences it acoustics. To give just one example, the round shape of the Echo Dot offers a full cavity behind the woofer for a better bass response.

Related content
NASA is using unsupervised learning and anomaly detection to explore the extreme conditions associated with solar superstorms.

However, when it came to NASA’s Orion spacecraft, Alexa’s acoustic engineers had to work with what was provided by Lockheed Martin and NASA.

“We were somewhat limited by the form factor, which was a small briefcase-like enclosure that was 1.5 feet by one foot and about five inches in depth.” says Lantin.

There were other physical constraints. Equipment developed for the mission had to be resilient to extreme shocks and vibrations, be at least minimally resistant to radiation emissions in space, and utilize highly specific and custom-built components such as power and data cables.

Limited Internet connectivity

The team also had to deal with issues related to the lack of Internet connectivity. Typically, Echo devices use on-device keyword spotting designed to detect when a customer says the wake word. This on-device buffer exists in temporary memory. After the wake word is detected, the device streams the audio to the cloud for speech recognition and natural language processing.

Orion components

“However, for the Orion mission, our ability to communicate with the Alexa cloud was severely constrained,” says Lantin. “NASA’s spacecraft uses the Deep Space Network to communicate with earth. The bandwidth available to us on the downlink connection is slightly better than dial-up modem speeds with latencies of up to five seconds. To further complicate matters, NASA prioritizes traffic for navigation and telemetry for the first payload — traffic for Alexa was consigned to the secondary payload.”

The team also wanted to demonstrate a fully autonomous experience, one that can be used in future missions where Earth connectivity is no longer a practical option for real-time communications. They used Alexa Local Voice Control to get around the limited internet connectivity. Alexa Local Voice control allows select devices to process voice commands locally, rather than sending information to the cloud.

Lantin says that while the team was motivated by demonstrating technology leadership and scientific innovation in a very challenging environment, the real motivator was making a difference in the lives of millions of customers at home on earth.

“At Amazon, we take pride in delivering customer-focused science,” says Lantin. “That was a huge motivator for us at every step along the way. Consider the innovations we drove to Alexa Local Voice Control. These improvements will allow people on earth to do so much more with Alexa in situations where they have limited or no Internet connectivity. Think about when you are in a car and passing through a tunnel, or driving to a remote camping site. You can do things like tune the radio, turn on the AC and continue to use voice commands, even if you have a feeble signal or no cellular connection.”

Lantin says that the acoustic innovations enabled for Orion will also translate directly into improved listening experiences for people interacting with the mission on earth.

Rohit Prasad, Alexa senior vice president and head scientist, on the initial collaboration with Lockheed Martin

“We are planning to have celebrities, politicians, STEM students and a variety of other personalities interacting with Alexa,” says Lantin. “ And so, we also spent a good deal of time thinking about what people might want to ask Alexa about during the mission.”

The nuances of acoustics aboard Orion

Scott Isabelle is a solutions architect at Amazon. Prior to Amazon, Isabelle was a distinguished member of the technical staff at Motorola, where among other projects, he developed systems for enhancing voice quality in mobile devices, methods for generating adaptive ringtones, and a two-microphone system for noise suppression.

“One of the most important things for a voice AI is being in an environment where it is able to pick up your voice,” says Isabelle.

Related content
Parallel processing of microphone inputs and separate detectors for periodicity and dynamics improve performance.

However, this is easier said than done on Orion, where the conical shape of the space capsule, and its metallic surfaces result in increased reverberation.

“The voice can keep bouncing around losing very little energy. This wouldn’t happen in a typical room where soft material like curtains and sofa cushions can absorb some of the sound. In the capsule, the reverberations off the metal surfaces can play up the wrong frequencies that are critical to automatic speech recognition. This can make it really difficult for Alexa to pick up wake word invocations. ”

Alexa also has to contend with increased noise levels aboard Orion.

NASA | Exploration Mission-1 — pushing farther into deep space

The ideal signal to noise ratio (SNR) for systems involving intelligent voice assistants is in the range 20 to 30 decibels (dB). To place this in context, a SNR of 35 dB is what you would find in a face-to-face conversation between two people standing one meter apart in a typical room (higher SNRs are better). However, the SNR onboard the Orion capsule can be much lower than 20 dB, posing an acoustic challenge.

To enhance the comfort of astronauts during crewed missions, NASA would ordinarily place acoustic blankets to damp down the reverberation in the hard-walled cabin, and some of the noise created by engines and pumps.

“However, because this is an uncrewed mission we have to work within an environment with more reverberation and noise than we would like,” says Isabelle.

re:MARS 2022 — Open space: A revolution in robots for space exploration

There’s another challenge that results from the lack of humans on board. For Orion, commands to Alexa have to be sent from ground control. The low-bandwidth connections utilized for the transmission can make it challenging to transmit voices at the wide range of frequencies essential for differentiating between sounds.

During a typical phone call, our voice is typically transmitted in the narrow band, which ranges from 300 HZ to 3,000 HZ. For Alexa to make out individual words aboard the noisier environment of the space capsule, the voice would have to be transmitted at 8,000 HZ.

“Voice commands from mission control are transmitted to Alexa via a speaker,” says Isabelle. “Flight-qualified speakers are typically designed for narrow-band communications. And so for this mission we were required to use a speaker that could operate in the flight environment.”

Alexa in Space | Alexa Innovators | Build with Alexa

The team relied on what Isabelle calls “brute force” to overcome these acoustic challenges.

Related content
A combination of audio and visual signals guide the device’s movement, so the screen is always in view.

“We designed the speaker playback system to play at extremely loud volumes, which allowed us to increase the SNR to where we wanted it to be.”

The team also took advantage of the physical form factor of Alexa on board to overcome the challenges presented by the noisy environment. The speakers, the light ring and the microphones in the briefcase-like enclosure for Alexa are close to each other, which allows acoustic engineers to overcome some of the obstacles presented by the background noise and reverberation.

Finally, the team deployed two microphones in combination with an array processing algorithm. The latter combined the signals from the two microphones in a way that helps Alexa make sense of the commands being issued from mission control. Because the speakers and microphones are in fixed positions relative to each other — as opposed to a room, where people can be located in any number of locations — the algorithms could be more easily designed to distinguish between speech and the surrounding noise.

Related content
Zoox principal software engineer Olivier Toupet on company’s autonomous robotaxi technology

While the Orion mission will not have any crew members on board, the initial mission will lay the groundwork for Alexa to be integrated into future crewed missions — to the moon, Mars, and beyond. Having Alexa onboard in these future missions would allow crew members to be more efficient in day-to-day tasks, and benefit from the comforts of having Alexa on board such as the ability to play relaxing music and to keep in touch with family and friends back home.

Future crewed missions would have their own unique set of challenges, where Alexa would have to respond to commands from astronauts, who might (literally) be free-floating at multiple points within the capsule. Isabelle and Lantin are already looking forward to overcoming the challenges enabled by crewed missions.

“For someone who grew up watching Star Trek, working on this project has been a dream come true,” says Lantin. “It’s great to be able to build the future. But it’s just as exciting to be able to draw on all of this great work, and be able to enjoy all these new Alexa capabilities during my next vacation, and my day-to-day life right here at home.”

Editor's note

This is a reprint of an article that initially ran on the Alexa Skills Kit Blog. To learn more about the technical innovations that helped get Alexa into space and some inspiring facts about the Artemis I mission, visit the Skills Kit blog.

Research areas

Related content

US, WA, Bellevue
The Artificial General Intelligence (AGI) team is looking for a passionate, talented, and inventive Senior Applied Scientist to work on methodologies for Generative Artificial Intelligence (GenAI) models. As a Senior Applied Scientist, you will be responsible for leading the development of novel algorithms and modeling techniques to advance the state of the art. Your work will directly impact our customers and will leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate development with multi-modal Large Language Models (LLMs) and GenAI. You will have significant influence on our overall strategy by working at the intersection of engineering and applied science to scale pre-training and post-training workflows and build efficient models. You will support the system architecture and the best practices that enable a quality infrastructure. Key job responsibilities Join us to work as an integral part of a team that has experience with GenAI models in this space. We work on these areas: - Pre-training and post-training multimodal LLMs - Scale training, optimization methods, and learning objectives - Utilize, build, and extend upon industry-leading frameworks - Work with other team members to investigate design approaches, prototype new technology, scientific techniques and evaluate technical feasibility - Deliver results independently in a self-organizing Agile environment while constantly embracing and adapting new scientific advances About the team The AGI team has a mission to push the envelope in GenAI with Large Language Models (LLMs) and multimodal systems, in order to provide the best-possible experience for our customers.
CA, BC, Vancouver
Join our Amazon Private Brands Selection Guidance organization in building science and tech solutions at scale to delight our customers with products across our leading private brands such as Amazon Basics, Amazon Essentials, and by Amazon. The Selection Guidance team applies Generative AI, Machine Learning, Statistics, and Economics solutions to drive our private brands product assortment, strategic business decisions, and product inputs such as title, price, merchandising and ordering. We are an interdisciplinary team of Scientists, Economists, Engineers, and Product Managers incubating and building day one solutions using novel technology, to solve some of the toughest business problems at Amazon. As a Sr. Data Scientist you will invent novel solutions and prototypes, and directly contribute to bringing your ideas to life through production implementation. Current research areas include entity resolution, agentic AI, large language models, and product substitutes. You will review and guide scientists across the team on their designs and implementations, and raise the team bar for science research and prototypes. This is a unique, high visibility opportunity for someone who wants to develop ambitious science solutions and have direct business and customer impact. Key job responsibilities - Partner with business stakeholders to deeply understand APB business problems and frame ambiguous business problems as science problems and solutions. - Invent novel science solutions, develop prototypes, and deploy production software to solve business problems. - Review and guide science solutions across the team. - Publish and socialize your and the team's research across Amazon and external avenues as appropriate - Leverage industry best practices to establish repeatable applied science practices, principles & processes.
US, WA, Seattle
We are looking for a passionate Applied Scientist to help pioneer the next generation of agentic AI applications for Amazon advertisers. In this role, you will design agentic architectures, develop tools and datasets, and contribute to building systems that can reason, plan, and act autonomously across complex advertiser workflows. You will work at the forefront of applied AI, developing methods for fine-tuning, reinforcement learning, and preference optimization, while helping create evaluation frameworks that ensure safety, reliability, and trust at scale. You will work backwards from the needs of advertisers—delivering customer-facing products that directly help them create, optimize, and grow their campaigns. Beyond building models, you will advance the agent ecosystem by experimenting with and applying core primitives such as tool orchestration, multi-step reasoning, and adaptive preference-driven behavior. This role requires working independently on ambiguous technical problems, collaborating closely with scientists, engineers, and product managers to bring innovative solutions into production. Key job responsibilities - Design and build agents to guide advertisers in conversational and non-conversational experience. - Design and implement advanced model and agent optimization techniques, including supervised fine-tuning, instruction tuning and preference optimization (e.g., DPO/IPO). - Curate datasets and tools for MCP. - Build evaluation pipelines for agent workflows, including automated benchmarks, multi-step reasoning tests, and safety guardrails. - Develop agentic architectures (e.g., CoT, ToT, ReAct) that integrate planning, tool use, and long-horizon reasoning. - Prototype and iterate on multi-agent orchestration frameworks and workflows. - Collaborate with peers across engineering and product to bring scientific innovations into production. - Stay current with the latest research in LLMs, RL, and agent-based AI, and translate findings into practical applications. About the team The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through the latest 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 Advertiser Guidance team within Sponsored Products and Brands is focused on guiding and supporting 1.6MM advertisers to meet their advertising needs of creating and managing ad campaigns. At this scale, the complexity of diverse advertiser goals, campaign types, and market dynamics creates both a massive technical challenge and a transformative opportunity: even small improvements in guidance systems can have outsized impact on advertiser success and Amazon’s retail ecosystem. Our vision is to build a highly personalized, context-aware agentic advertiser guidance system that leverages LLMs together with tools such as auction simulations, ML models, and optimization algorithms. This agentic framework, will operate across both chat and non-chat experiences in the ad console, scaling to natural language queries as well as proactively delivering guidance based on deep understanding of the advertiser. To execute this vision, we collaborate closely with stakeholders across Ad Console, Sales, and Marketing to identify opportunities—from high-level product guidance down to granular keyword recommendations—and deliver them through a tailored, personalized experience. Our work is grounded in state-of-the-art agent architectures, tool integration, reasoning frameworks, and model customization approaches (including tuning, MCP, and preference optimization), ensuring our systems are both scalable and adaptive.
US, CA, Pasadena
The Amazon Web Services (AWS) Center for Quantum Computing (CQC) is a multi-disciplinary team of scientists, engineers, and technicians on a mission to develop a fault-tolerant quantum computer. You will be joining a team located in Pasadena, CA that conducts materials research to improve the performance of superconducting quantum processors. We seek a Quantum Research Scientist to investigate how material defects affect qubit performance. In this role, you will combine expertise in numerical simulations and materials characterization to study materials loss mechanisms such as two-level systems, quasiparticles, vortices, etc. Key job responsibilities Provide subject matter expertise on integrated experimental and computational studies of materials defects Develop and use computational tools for large-scale simulations of disordered structures Develop and implement multi-technique materials characterization workflows for thin films and devices, with a focus on the surfaces and interfaces Identify material properties that can be a reliable proxy for the performance of superconducting resonators and qubits Communicate findings to teammates, the broader CQC team and, when appropriate, publish findings in scientific journals A day in the life At the AWS CQC, we understand that developing quantum computing technology is a marathon, not a sprint. The work/life integration within our team encourages a culture where employees work hard and also have ownership over their downtime. We are committed to the growth and development of every employee at the AWS CQC, and that includes our research scientists. You will receive management and mentorship from within the team that is geared toward career growth, and also have the opportunity to participate in Amazon's mentorship programs for scientists and engineers. Working closely with other quantum research scientists in other disciplines – like design, measurement and cryogenic hardware – will provide opportunities to dive deep into an education on quantum computing. About the team Our team contributes to the fabrication of processors and other hardware that enable quantum computing technologies. Doing that necessitates the development of materials with tailored properties for superconducting circuits. Research Scientists and Engineers on the Materials team operate deposition and characterization systems in order to develop and optimize thin film processes for use in these devices. They work alongside other Research Scientists and Engineers to help deliver the fabricated devices for quantum computing experiments. Export Control Requirement: Due to applicable export control laws and regulations, candidates must be either a U.S. citizen or national, U.S. permanent resident (i.e., current Green Card holder), or lawfully admitted into the U.S. as a refugee or granted asylum, or be able to obtain a U.S export license. If you are unsure if you meet these requirements, please apply and Amazon will review your application for eligibility. About the team 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 AWS values curiosity and connection. Our employee-led and company-sponsored affinity groups promote inclusion and empower our people to take pride in what makes us unique. Our inclusion events foster stronger, more collaborative teams. Our continual innovation is fueled by the bold ideas, fresh perspectives, and passionate voices our teams bring to everything we do. 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. Export Control Requirement: Due to applicable export control laws and regulations, candidates must be either a U.S. citizen or national, U.S. permanent resident (i.e., current Green Card holder), or lawfully admitted into the U.S. as a refugee or granted asylum, or be able to obtain a U.S export license. If you are unsure if you meet these requirements, please apply and Amazon will review your application for eligibility.
US, CA, Sunnyvale
Prime Video is a first-stop entertainment destination offering customers a vast collection of premium programming in one app available across thousands of devices. Prime members can customize their viewing experience and find their favorite movies, series, documentaries, and live sports – including Amazon MGM Studios-produced series and movies; licensed fan favorites; and programming from Prime Video add-on subscriptions such as Apple TV+, Max, Crunchyroll and MGM+. All customers, regardless of whether they have a Prime membership or not, can rent or buy titles via the Prime Video Store, and can enjoy even more content for free with ads. Are you interested in shaping the future of entertainment? Prime Video's technology teams are creating best-in-class digital video experience. As a Prime Video technologist, you’ll have end-to-end ownership of the product, user experience, design, and technology required to deliver state-of-the-art experiences for our customers. You’ll get to work on projects that are fast-paced, challenging, and varied. You’ll also be able to experiment with new possibilities, take risks, and collaborate with remarkable people. We’ll look for you to bring your diverse perspectives, ideas, and skill-sets to make Prime Video even better for our customers. With global opportunities for talented technologists, you can decide where a career Prime Video Tech takes you! Key job responsibilities - Develop ML models for various recommendation & search systems using deep learning, online learning, and optimization methods - Work closely with other scientists, engineers and product managers to expand the depth of our product insights with data, create a variety of experiments to determine the high impact projects to include in planning roadmaps - Stay up-to-date with advancements and the latest modeling techniques in the field - Publish your research findings in top conferences and journals A day in the life We're using advanced approaches such as foundation models to connect information about our videos and customers from a variety of information sources, acquiring and processing data sets on a scale that only a few companies in the world can match. This will enable us to recommend titles effectively, even when we don't have a large behavioral signal (to tackle the cold-start title problem). It will also allow us to find our customer's niche interests, helping them discover groups of titles that they didn't even know existed. We are looking for creative & customer obsessed machine learning scientists who can apply the latest research, state of the art algorithms and ML to build highly scalable page personalization solutions. You'll be a research leader in the space and a hands-on ML practitioner, guiding and collaborating with talented teams of engineers and scientists and senior leaders in the Prime Video organization. You will also have the opportunity to publish your research at internal and external conferences. About the team Prime Video Recommendation Science team owns science solution to power recommendation and personalization experience on various Prime Video surfaces and devices. We work closely with the engineering teams to launch our solutions in production.
US, CA, Sunnyvale
Prime Video is a first-stop entertainment destination offering customers a vast collection of premium programming in one app available across thousands of devices. Prime members can customize their viewing experience and find their favorite movies, series, documentaries, and live sports – including Amazon MGM Studios-produced series and movies; licensed fan favorites; and programming from Prime Video add-on subscriptions such as Apple TV+, Max, Crunchyroll and MGM+. All customers, regardless of whether they have a Prime membership or not, can rent or buy titles via the Prime Video Store, and can enjoy even more content for free with ads. Are you interested in shaping the future of entertainment? Prime Video's technology teams are creating best-in-class digital video experience. As a Prime Video technologist, you’ll have end-to-end ownership of the product, user experience, design, and technology required to deliver state-of-the-art experiences for our customers. You’ll get to work on projects that are fast-paced, challenging, and varied. You’ll also be able to experiment with new possibilities, take risks, and collaborate with remarkable people. We’ll look for you to bring your diverse perspectives, ideas, and skill-sets to make Prime Video even better for our customers. With global opportunities for talented technologists, you can decide where a career Prime Video Tech takes you! Key job responsibilities - Develop ML models for various recommendation & search systems using deep learning, online learning, and optimization methods - Work closely with other scientists, engineers and product managers to expand the depth of our product insights with data, create a variety of experiments to determine the high impact projects to include in planning roadmaps - Stay up-to-date with advancements and the latest modeling techniques in the field - Publish your research findings in top conferences and journals A day in the life We're using advanced approaches such as foundation models to connect information about our videos and customers from a variety of information sources, acquiring and processing data sets on a scale that only a few companies in the world can match. This will enable us to recommend titles effectively, even when we don't have a large behavioral signal (to tackle the cold-start title problem). It will also allow us to find our customer's niche interests, helping them discover groups of titles that they didn't even know existed. We are looking for creative & customer obsessed machine learning scientists who can apply the latest research, state of the art algorithms and ML to build highly scalable page personalization solutions. You'll be a research leader in the space and a hands-on ML practitioner, guiding and collaborating with talented teams of engineers and scientists and senior leaders in the Prime Video organization. You will also have the opportunity to publish your research at internal and external conferences. About the team Prime Video Recommendation Science team owns science solution to power recommendation and personalization experience on various Prime Video surfaces and devices. We work closely with the engineering teams to launch our solutions in production.
US, CA, Sunnyvale
Prime Video is a first-stop entertainment destination offering customers a vast collection of premium programming in one app available across thousands of devices. Prime members can customize their viewing experience and find their favorite movies, series, documentaries, and live sports – including Amazon MGM Studios-produced series and movies; licensed fan favorites; and programming from Prime Video add-on subscriptions such as Apple TV+, Max, Crunchyroll and MGM+. All customers, regardless of whether they have a Prime membership or not, can rent or buy titles via the Prime Video Store, and can enjoy even more content for free with ads. Are you interested in shaping the future of entertainment? Prime Video's technology teams are creating best-in-class digital video experience. As a Prime Video technologist, you’ll have end-to-end ownership of the product, user experience, design, and technology required to deliver state-of-the-art experiences for our customers. You’ll get to work on projects that are fast-paced, challenging, and varied. You’ll also be able to experiment with new possibilities, take risks, and collaborate with remarkable people. We’ll look for you to bring your diverse perspectives, ideas, and skill-sets to make Prime Video even better for our customers. With global opportunities for talented technologists, you can decide where a career Prime Video Tech takes you! We are looking for a self-motivated, passionate and resourceful Applied Scientist to bring diverse perspectives, ideas, and skill-sets to make Prime Video even better for our customers. You will spend your time as a hands-on machine learning practitioner and a research leader. You will play a key role on the team, building and guiding machine learning models from the ground up. At the end of the day, you will have the reward of seeing your contributions benefit millions of Amazon.com customers worldwide. Key job responsibilities - Develop AI solutions for various Prime Video Search systems using Deep learning, GenAI, Reinforcement Learning, and optimization methods; - Work closely with engineers and product managers to design, implement and launch AI solutions end-to-end; - Design and conduct offline and online (A/B) experiments to evaluate proposed solutions based on in-depth data analyses; - Effectively communicate technical and non-technical ideas with teammates and stakeholders; - Stay up-to-date with advancements and the latest modeling techniques in the field; - Publish your research findings in top conferences and journals. About the team Prime Video Search Science team owns science solution to power search experience on various devices, from sourcing, relevance, ranking, to name a few. We work closely with the engineering teams to launch our solutions in production.
US, CA, Sunnyvale
Prime Video is a first-stop entertainment destination offering customers a vast collection of premium programming in one app available across thousands of devices. Prime members can customize their viewing experience and find their favorite movies, series, documentaries, and live sports – including Amazon MGM Studios-produced series and movies; licensed fan favorites; and programming from Prime Video add-on subscriptions such as Apple TV+, Max, Crunchyroll and MGM+. All customers, regardless of whether they have a Prime membership or not, can rent or buy titles via the Prime Video Store, and can enjoy even more content for free with ads. Are you interested in shaping the future of entertainment? Prime Video's technology teams are creating best-in-class digital video experience. As a Prime Video technologist, you’ll have end-to-end ownership of the product, user experience, design, and technology required to deliver state-of-the-art experiences for our customers. You’ll get to work on projects that are fast-paced, challenging, and varied. You’ll also be able to experiment with new possibilities, take risks, and collaborate with remarkable people. We’ll look for you to bring your diverse perspectives, ideas, and skill-sets to make Prime Video even better for our customers. With global opportunities for talented technologists, you can decide where a career Prime Video Tech takes you! We are looking for a self-motivated, passionate and resourceful Applied Scientist to bring diverse perspectives, ideas, and skill-sets to make Prime Video even better for our customers. You will spend your time as a hands-on machine learning practitioner and a research leader. You will play a key role on the team, building and guiding machine learning models from the ground up. At the end of the day, you will have the reward of seeing your contributions benefit millions of Amazon.com customers worldwide. Key job responsibilities - Develop AI solutions for various Prime Video Search systems using Deep learning, GenAI, Reinforcement Learning, and optimization methods; - Work closely with engineers and product managers to design, implement and launch AI solutions end-to-end; - Design and conduct offline and online (A/B) experiments to evaluate proposed solutions based on in-depth data analyses; - Effectively communicate technical and non-technical ideas with teammates and stakeholders; - Stay up-to-date with advancements and the latest modeling techniques in the field; - Publish your research findings in top conferences and journals. About the team Prime Video Search Science team owns science solution to power search experience on various devices, from sourcing, relevance, ranking, to name a few. We work closely with the engineering teams to launch our solutions in production.
US, CA, Cupertino
We are seeking a highly skilled Data Scientist to join our Machine Learning Architecture team, focusing on power and performance optimization for ML acceleration workloads across Amazon's global data center infrastructure. This role combines advanced data science techniques with deep technical understanding of ML hardware acceleration to drive efficiency improvements in training and inference workloads at massive scale. Key job responsibilities ata Analysis & Optimization * Analyze power consumption and performance metrics across all Amazon data centers for machine learning acceleration workloads * Develop predictive models and statistical frameworks to identify optimization opportunities and performance bottlenecks * Create automated monitoring and alerting systems for power and performance anomalies Strategic Planning & Deployment Guidance * Provide data-driven recommendations for server deployments and capacity planning decisions across Amazon's global data center network * Develop optimization scenarios and business cases to improve capacity delivery efficiency to customers worldwide * Support strategic decision-making through comprehensive analysis of power, performance, and cost trade-offs Cross-Functional Collaboration * Partner with software engineering teams to optimize ML frameworks, drivers, and runtime systems * Collaborate with hardware engineering teams to influence chip design, server architecture, and cooling system optimization * Work closely with data center operations teams to implement and validate optimization strategies Research & Development * Conduct applied research on emerging ML acceleration technologies and their power/performance characteristics * Develop novel methodologies for measuring and improving energy efficiency in large-scale ML workloads * Publish findings and contribute to industry best practices in sustainable ML infrastructure
IN, KA, Bengaluru
Amazon Devices is an inventive research and development company that designs and engineer high-profile devices like the Kindle family of products, Fire Tablets, Fire TV, Health Wellness, Amazon Echo & Astro products. This is an exciting opportunity to join Amazon in developing state-of-the-art techniques that bring Gen AI on edge for our consumer products. We are looking for exceptional scientists to join our Applied Science team and help develop the next generation of edge models, and optimize them while doing co-designed with custom ML HW based on a revolutionary architecture. Work hard. Have Fun. Make History. Key job responsibilities What will you do? - Quantize, prune, distill, finetune Gen AI models to optimize for edge platforms - Fundamentally understand Amazon’s underlying Neural Edge Engine to invent optimization techniques - Analyze deep learning workloads and provide guidance to map them to Amazon’s Neural Edge Engine - Use first principles of Information Theory, Scientific Computing, Deep Learning Theory, Non Equilibrium Thermodynamics - Train custom Gen AI models that beat SOTA and paves path for developing production models - Collaborate closely with compiler engineers, fellow Applied Scientists, Hardware Architects and product teams to build the best ML-centric solutions for our devices - Publish in open source and present on Amazon's behalf at key ML conferences - NeurIPS, ICLR, MLSys.