Orbital Systems makes sustainable water use something people can enjoy

Mehrdad Mahdjoubi, founder and CEO of Alexa Fund portfolio company, explains "no compromise" approach to saving resources without sacrificing user experience.

(Editor’s note: This article is the latest installment in a series by Amazon Science delving into the science behind products and services of companies in which Amazon has invested. The Alexa Fund invested in Orbital Systems in April 2022.)

Americans use an average of 60 gallons of clean water per person inside their homes each day, nearly half of which goes to toilets and showers. Low-flow fixtures and other conservation strategies have reduced per-capita consumption since the 1980s. But the scarcity of water on Earth — less than 1% of the water on our planet is drinkable — demands that we use it more wisely.

Orbital Systems founder and CEO Mehrdad Mahdjoubi
Orbital Systems founder and CEO Mehrdad Mahdjoubi said his work with NASA on a plan for human habitation on Mars inspired his thinking when he launched Orbital.

Orbital Systems aims to meet this demand with products inspired by a setting where water is even more scarce: Mars.

As a master’s student in industrial design, founder and CEO Mehrdad Mahdjoubi collaborated with NASA scientists on a plan for long-term human habitation on Mars.

“The limitations on available resources meant that we had to be creative,” Mahdjoubi says.

He realized that other essential resources, like energy and nutrients, tend to flow in a circular manner. “With energy, we have the sun. Nutrients cycle between the physical environment and living organisms. But water use is not like that,” Mahdjoubi explains.

Mahdjoubi started Orbital Systems in 2012 to develop resource-saving products for consumers on Earth. The Orbital Shower was the first product to launch. The shower starts with less than a gallon of water, and the system checks the water quality 20 times per second during operation. Water too contaminated to be reused is discarded and replaced, and the rest is filtered and exposed to ultraviolet light before being recirculated. Because the recirculated water is warm, it requires much less energy for heating. The Orbital Shower uses up to 90% less water and 80% less energy than a conventional shower.

Next came the Orbital Tap, which reuses water from a sink to flush a toilet. “It’s a solution to the age-old problem of flushing clean drinking water down the toilet,” Mahdjoubi says.

Sustainability
Pioneering web-based PackOpt tool has resulted in an annual reduction in cardboard waste of 7% to 10% in North America, saving roughly 60,000 tons of cardboard annually.

Orbital products are available to hotel chains, real-estate developers, and individual consumers in Sweden, Denmark, and Germany. Mahdjoubi is seeking partners and installers to enable expansion to markets in North America and beyond.

Orbital users can start a customized shower — lighting, music, flow, temperature, duration, etc. — with a single command via an Alexa integration.

Mahdjoubi spoke with Amazon Science about water use from Mars to ancient Rome to our own bathrooms and what differentiates Orbital Systems’ products from other resource-saving strategies.

  1. Q. 

    What inspired you to design sustainable water systems for Mars and implement them on Earth?

    A. 

    While I was studying industrial design at Lund University, I had the opportunity to go to Johnson Space Center and take part in a project with NASA. The goal was to enable an earthly living standard on Mars.

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

    Establishing a Mars colony required us to solve a lot of issues related to resource management, given the strict resource limitations.

    There are three resources that humans need in addition to oxygen. One is energy, the second is water, and the third is nutrients. I started looking at how we handle resources on Earth, and how we might translate the positive aspects to a new setting without repeating the more foolish aspects.

    Every resource has a supply side and a demand side. In the energy sector, we’ve walked a pretty long way on the demand side. A hundred or two hundred years ago, all of our focus in energy was on the supply side: pump up more oil, pump up more gas, produce more. Then around the second oil crisis in the ‘70s, there was a massive realization that we can’t just focus on pumping up more, creating more energy. We need to think about how we use it.

    The Orbital Shower mobile app is seen on a smartphone screen displaying 370 liters of water saved, the phone is sitting on a towel
    Orbital's CEO says their system "starts with technical innovation that actually reduces water and energy use and then tracks the savings through a digital interface."

    Fast forward to today, we have much more focus on the demand side. There’s an understanding that we can do a lot more if we just don’t waste the energy we make. Many of the products we buy are energy efficient: fridges, TVs, LED lights.

    Then I looked at water and found the way we use water now is practically no different from the Roman aqueducts of 2,000 or 3,000 years ago. We find water somewhere, and if it’s clean, we pump it to houses. If it’s not clean, we treat it first. We haven’t really changed anything since the Romans. I mean, we flush toilets with drinking water. We haven’t done anything to optimize the demand side.

    So when it comes to building a new habitat on Mars, what are we not going to do? We’re not going to generate drinking water — which we do out of air, pretty expensive — and then pour it down a drain or flush it down a toilet.

    That was the background, back in 2012. At the time, the mission launch was set to 2035 and the shower project was mostly at the conceptual level. I felt there was no reason to wait 20 years to develop a product for eight astronauts when there is an urgent need and much bigger opportunity on Earth.

    I moved back to Sweden, where I was born and raised, started Orbital Systems, and got research funding to come up with functioning prototypes. Today we’ve raised north of a hundred million dollars and have a team of almost 100 people.

  2. Q. 

    How did you approach the product design, and what were the biggest challenges?

    A. 

    What attracted me as a product designer is that this is a rare "no compromise" solution. You can save water and energy and you get a really, really nice shower experience. If you were to ask yourself what constitutes a nice shower, it comes down to three factors. Number one is clean water, number two is flow rate, and number three is temperature stability. We outperform conventional showers on all three points.

    Achieving sustainability
    How data-driven methods can help to identify fault detection and drive energy efficiencies for facilities of all sizes.

    One challenge in creating that experience was to make everything seamlessly work together. We’re talking about 350 individual components. It’s a multidisciplinary system where you have to control everything, including thermodynamics, software, pumping fluid dynamics, temperature sensors, pressure sensors, filtration, and electronics. We had to develop our own water quality sensors, figure out how to handle soap, and those kinds of things.

    And we wanted to hide the tech. People want to feel the bathroom is a nice relaxing area, not a tech lab. So we needed to spend the time and energy to make it invisible. In an Orbital Shower, aside from the control dial and digital display, there’s no way you would guess what’s going on in the background.

    Adapting to customer needs
    Scientists updated the system to accurately measure body fat percentage and create personalized 3D models even if there’s not enough room to take a full-body photo.

    A key technical challenge that we had to overcome was filtration. Most filters that can trap bacteria and viruses are exceedingly slow. We use filtration technology, developed with NASA funding, that is ultra-effective but very fast, coupled with ultraviolet light for disinfection.

    Another challenge was that it needed to be easy to install. We wanted to make sure that our products could fit in any bathroom, whether the wall is made of bricks or plaster. A lot of effort was spent to accommodate different circumstances and building methods. We offer retrofit models that can be installed in existing bathrooms, as well as models meant for new installation.

  3. Q. 

    How is Orbital technology different from other ‘smart water’ systems?

    A. 

    First, if you look into water technologies in general, the majority has been done at the utility level, like desalination plants, water treatment plans, that kind of stuff. Much less has been done for the end consumer, and most of that has targeted drinking water, which is a tiny fraction of the water we use.

    That said, technology for low-flow showers and toilets has existed for like 40 years or so and still not become super popular, because the quality of the experience is compromised. We are going at it the other way. I think, personally, to find scalable solutions, we need to focus on the ‘no compromise’ ones.

    Then there are smart water systems that are all about data, informing consumers about their water use with the goal of changing behaviors to save water. Several of our clients told us they had tried such ‘awareness solutions’ before but fell into despair, because they felt they couldn’t do enough.

    An Orbital Shower control dial with a digital reading showing 91.3 liters saved is seen, a person's hand is seen is pointing to the dial
    The Orbital Shower starts with less than a gallon of water, and the system checks the water quality 20 times per second during operation.

    Orbital starts with technical innovation that actually reduces water and energy use and then tracks the savings through a digital interface.

    The digital interface also features an Alexa integration where you can start your perfect shower with a single command, coordinating the Orbital Shower with other smart-home features like lighting, room temperature, window dressings, music, et cetera.

    I think people want to maximize their experience — like taking a long shower — without being wasteful, to be responsible and live sustainably but also have a pleasant experience. Why shouldn’t we have both?

Research areas

Related content

US, WA, Seattle
Do you want to join an innovative team of scientists who use machine learning to help Amazon provide the best experience to our Selling Partners by automatically understanding and addressing their challenges, needs and opportunities? Do you want to build advanced algorithmic systems that are powered by state-of-art ML, such as Natural Language Processing, Large Language Models, Deep Learning, Computer Vision and Causal Modeling, to seamlessly engage with Sellers? Are you excited by the prospect of analyzing and modeling terabytes of data and creating cutting edge algorithms to solve real world problems? Do you like to build end-to-end business solutions and directly impact the profitability of the company and experience of our customers? Do you like to innovate and simplify? If yes, then you may be a great fit to join the Selling Partner Experience Science team. Key job responsibilities - Use statistical and machine learning techniques to create the next generation of the tools that empower Amazon's Selling Partners to succeed. - Design, develop and deploy highly innovative models to interact with Sellers and delight them with solutions. - Work closely with teams of scientists and software engineers to drive real-time model implementations and deliver novel and highly impactful features. - Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation. - Research and implement novel machine learning and statistical approaches. - Participate in strategic initiatives to employ the most recent advances in ML in a fast-paced, experimental environment. About the team Selling Partner Experience Science is a growing team of scientists, engineers and product leaders engaged in the research and development of the next generation of ML-driven technology to empower Amazon's Selling Partners to succeed. We draw from many science domains, from Natural Language Processing to Computer Vision to Optimization to Economics, to create solutions that seamlessly and automatically engage with Sellers, solve their problems, and help them grow. Focused on collaboration, innovation and strategic impact, we work closely with other science and technology teams, product and operations organizations, and with senior leadership, to transform the Selling Partner experience. We are open to hiring candidates to work out of one of the following locations: Denver, CO, USA | Seattle, WA, USA
US, WA, Seattle
Amazon is investing heavily in building a world class advertising business and developing a collection of self-service performance advertising products that drive discovery and sales. Our products are strategically important to our Retail and Marketplace businesses for driving long-term growth. We deliver billions of ad impressions and millions of clicks daily and are breaking fresh ground to create world-class products. We are highly motivated, collaborative and fun-loving with an entrepreneurial spirit and bias for action. With a broad mandate to experiment and innovate, we are growing at an unprecedented rate with a seemingly endless range of new opportunities. Key job responsibilities Search Supply and Experiences, within Sponsored Products, is seeking a Senior Data Scientist to join a fast growing team with the mandate of creating new ads experience that elevates the shopping experience for our hundreds of millions customers worldwide. We are looking for a top analytical mind capable of understanding our complex ecosystem of advertisers participating in a pay-per-click model– and leveraging this knowledge to help turn the flywheel of the business. As a Senior Data Scientist on this team you will: - Lead Data Science solutions from beginning to end. - Deliver with independence on challenging large-scale problems with ambiguity. - Manage and drive the technical and analytical aspects of Advertiser segmentation; continually advance approach and methods. - Write code (Python, R, Scala, etc.) to analyze data and build statistical models to solve specific business problems - Retrieve, synthesize, and present critical data in a format that is immediately useful to answering specific questions or improving system performance. - Analyze historical data to identify trends and support decision making. - Improve upon existing methodologies by developing new data sources, testing model enhancements, and fine-tuning model parameters. - Provide requirements to develop analytic capabilities, platforms, and pipelines. - Apply statistical and machine learning knowledge to specific business problems and data. - Formalize assumptions about how our systems should work, create statistical definitions of outliers, and develop methods to systematically identify outliers. Work out why such examples are outliers and define if any actions needed. - Given anecdotes about anomalies or generate automatic scripts to define anomalies, deep dive to explain why they happen, and identify fixes. - Build decision-making models and propose solution for the business problem you defined - Conduct written and verbal presentation to share insights and recommendations to audiences of varying levels of technical sophistication. - Write code (python or another object-oriented language) for data analyzing and modeling algorithms. A day in the life The Senior Data Scientist will have the opportunity to use one of the world's largest eCommerce and advertising data sets to influence the evolution of our products. This role requires an individual with excellent business, communication, and technical skills, enabling collaboration with various functions, including product managers, software engineers, economists and data scientists, as well as senior leadership. This role will create and enhance performance monitoring reports to find insights that product and business team should focus on. The successful candidate will be a self-starter comfortable with ambiguity, with strong attention to detail, and with an ability to work in a fast-paced, high-energy and ever-changing environment. The drive and capability to shape the direction is a must. This role will influence the direction of the business by leveraging our data to deliver insights that drive decisions and actions. The role will involve translating broad business problems into specific analytics projects, conducting deep quantitative analyses, and communicating results effectively. The role will help the organization identify, evaluate, and evangelize new techniques and tools to continue to improve our ability to deliver value to Amazon’s customers. About the team We are a customer-obsessed team of engineers, technologists, product leaders, and scientists. We are focused on continuous exploration of contexts and creatives where advertising delivers value to customers and advertisers. We specifically work on new ads experiences globally with the goal of helping shoppers make the most informed purchase decision. We obsess about our customers and we are continuously innovating on their behalf to enrich their shopping experience on Amazon We are open to hiring candidates to work out of one of the following locations: Seattle, WA, USA
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. We are looking to hire an Applied Scientist to work on the embedded software for our control system. The position is on-site at our lab, located on the Caltech campus in Pasadena, CA. The ideal candidate will be able to translate high-level requirements (e.g. latency, bandwidth, architecture) into software/firmware implementations (e.g. low-level device drivers, kernel modules, Python APIs) compatible with our FPGA-based control systems. This requires someone who (1) has a strong desire to work within a team of scientists and engineers, and (2) demonstrates ownership in initiating and driving projects to completion. Key job responsibilities - Develop embedded software in C, C++ or Rust for high-performance real-time tasks. - Develop Linux and/or real-time operating system (RTOS) features required to operate control system. - Develop FPGA gateware that drives domain-specific functions of our control hardware. - Develop user-space API that exposes low-level features, preferably in Python. - Develop, test, and optimize control system features on bench-top and in real-world conditions. - Own the stability of control system software and firmware. We are looking for candidates with strong engineering principles, resourcefulness and a bias for action, superior problem-solving and excellent communication skills. Working effectively within a team environment is essential. You will have the opportunity to work on new ideas and stay abreast of the field of experimental quantum computation. A day in the life The lifetime of your projects will likely begin with a lot of discussion and negotiation with our scientists and engineers to translate their software and hardware feature requests into design proposals that demonstrate sensible trade-offs between complexity and delivery. Once a design proposal has been accepted, you will implement it in a logical and maintainable manner. You will also be encouraged to take ownership over the stability and quality of the software and hardware stack by identifying, proposing, and implementing features that will accelerate our realization of quantum computing technologies. You will be joining the Control & Calibration Software team within the AWS Center of Quantum Computing. Our team is comprised of scientists and engineers who are building scalable software that enables quantum computing technologies. About the team AWS Utility Computing (UC) provides product innovations — from foundational services such as Amazon’s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS’s services and features apart in the industry. As a member of the UC organization, you’ll support the development and management of Compute, Database, Storage, Internet of Things (Iot), Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for their cloud services. Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Mentorship & Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. Hybrid Work We value innovation and recognize this sometimes requires uninterrupted time to focus on a build. We also value in-person collaboration and time spent face-to-face. Our team affords employees options to work in the office every day or in a flexible, hybrid work model near one of our U.S. Amazon offices. We are open to hiring candidates to work out of one of the following locations: Pasadena, CA, USA
US, WA, Seattle
Alexa is the Amazon cloud service that powers Echo, the groundbreaking Amazon device designed around your voice. We believe voice is the most natural user interface for interacting with technology across many domains; we are inventing the future. Alexa Audio is responsible for fulfilling customers requests for all types of audio content (Music, Radio, Podcasts, Books, custom sounds) across all Alexa enabled devices. This covers a broad set of experiences including search, browse, recommendations, playback, and devices grouping and controls. We are seeking a talented, self-directed Applied Scientists who would come up with state of the art semantic search and recommendation techniques that work with both voice and visual interfaces. This is a unique opportunity where you will be working on latest technologies including LLMs, and also see it impact customer's lives in meaningful ways. Responsibilities - Apply advance state-of-the-art artificial intelligence techniques and develop algorithms in areas of personalization, voice based dialogue systems and natural language information retrieval. - Design scientifically sound online experiments and offline simulations to study and improve products. - Work closely with talented engineers to create scalable models and put them to production. - Perform statistical analyses on large data sets, identify problems, and propose solutions. - Work with partner science teams to identify collaboration opportunities. Work hard. Have fun. Make history. We are open to hiring candidates to work out of one of the following locations: Bellevue, WA, USA | Seattle, WA, USA | Sunnyvale, CA, USA
GB, London
Amazon Advertising is looking for an Applied Scientist to join its initiative that powers Amazon’s contextual advertising products. Advertising at Amazon is a fast-growing multi-billion dollar business that spans across desktop, mobile and connected devices; encompasses ads on Amazon and a vast network of hundreds of thousands of third party publishers; and extends across US, EU and an increasing number of international geographies.The Supply Quality organization has the charter to solve optimization problems for ad-programs in Amazon and ensure high-quality ad-impressions. We develop advanced algorithms and infrastructure systems to optimize performance for our advertisers and publishers. We are focused on solving a wide variety of problems in computational advertising like Contextual data processing and classification, traffic quality prediction (robot and fraud detection), Security forensics and research, Viewability prediction, Brand Safety and experimentation. Our team includes experts in the areas of distributed computing, machine learning, statistics, optimization, text mining, information theory and big data systems. We are looking for a dynamic, innovative and accomplished Applied Scientist to work on machine learning and data science initiatives for contextual data processing and classification that power our contextual advertising solutions. Are you excited by the prospect of analyzing terabytes of data and leveraging state-of-the-art data science and machine learning techniques to solve real world problems? Do you like to own business problems/metrics of high ambiguity where yo get to define the path forward for success of a new initiative? As an applied scientist, you will invent ML based solutions to power our contextual classification technology. As this is a new initiative, you will get an opportunity to act as a thought leader, work backwards from the customer needs, dive deep into data to understand the issues, conceptualize and build algorithms and collaborate with multiple cross-functional teams. Key job responsibilities * Design, prototype and test many possible hypotheses in a high-ambiguity environment, making use of both analysis and business judgment. * Collaborate with software engineering teams to integrate successful experiments into large-scale, highly complex Amazon production systems. * Promote the culture of experimentation and applied science at Amazon. * Demonstrated ability to meet deadlines while managing multiple projects. * Excellent communication and presentation skills working with multiple peer groups and different levels of management * Influence and continuously improve a sustainable team culture that exemplifies Amazon’s leadership principles. We are open to hiring candidates to work out of one of the following locations: London, GBR
ES, M, Madrid
Amazon's International Technology org in EU (EU INTech) is creating new ways for Amazon customers discovering Amazon catalog through new and innovative Customer experiences. Our vision is to provide the most relevant content and CX for their shopping mission. We are responsible for building the software and machine learning models to surface high quality and relevant content to the Amazon customers worldwide across the site. The team, mainly located in Madrid Technical Hub, London and Luxembourg, comprises Software Developer and ML Engineers, Applied Scientists, Product Managers, Technical Product Managers and UX Designers who are experts on several areas of ranking, computer vision, recommendations systems, Search as well as CX. Are you interested on how the experiences that fuel Catalog and Search are built to scale to customers WW? Are interesting on how we use state of the art AI to generate and provide the most relevant content? Key job responsibilities We are looking for Applied Scientists who are passionate to solve highly ambiguous and challenging problems at global scale. You will be responsible for major science challenges for our team, including working with text to image and image to text state of the art models to scale to enable new Customer Experiences WW. You will design, develop, deliver and support a variety of models in collaboration with a variety of roles and partner teams around the world. You will influence scientific direction and best practices and maintain quality on team deliverables. We are open to hiring candidates to work out of one of the following locations: Madrid, M, ESP
DE, Berlin
The Amazon Artificial General Intelligence (AGI) team is looking for a passionate, highly skilled and inventive Senior Applied Scientist with strong machine learning background to lead the development and implementation of state-of-the-art ML systems for building large-scale, high-quality conversational assistant systems. Key job responsibilities - Use deep learning, ML and NLP techniques to create scalable solutions for creation and development of language model centric solutions for building personalized assistant systems based on a rich set of structured and unstructured contextual signals - Innovate new methods for contextual knowledge extraction and information representation, using language models in combination with other learning techniques, that allows effective grounding in context providers when considering memory, cpu, latency and quality - Collaborate with cross-functional teams of engineers, product managers, and scientists to identify and solve complex problems in personal knowledge aggregation, processing and verification - Design and execute experiments to evaluate the performance of different algorithms and models, and iterate quickly to improve results - Think Big about the arc of development of conversational assistant system personalization over a multi-year horizon, and identify new opportunities to apply these technologies to solve real-world problems - Communicate results and insights to both technical and non-technical audiences, including through presentations and written reports - Mentor and guide junior scientists and engineers, and contribute to the overall growth and development of the team A day in the life As a Senior Applied Scientist, you will play a critical role in driving the development of personalization techniques enabling conversational systems, in particular those based on large language models, to be tailored to customer needs. You will handle Amazon-scale use cases with significant impact on our customers' experiences. We are open to hiring candidates to work out of one of the following locations: Berlin, DEU
US, WA, Bellevue
Conversational AI ModEling and Learning (CAMEL) team is part of Amazon Artificial General Intelligence (AGI) organization where our mission is to create a best-in-class Conversational AI that is intuitive, intelligent, and responsive, by developing superior Large Language Models (LLM) solutions and services which increase the capabilities built into the model and which enable utilizing thousands of APIs and external knowledge sources to provide the best experience for each request across millions of customers and endpoints. We are looking for a passionate, talented, and resourceful Applied Scientist in the field of LLM, Artificial Intelligence (AI), Natural Language Processing (NLP), Recommender Systems and/or Information Retrieval, to invent and build scalable solutions for a state-of-the-art context-aware conversational AI. A successful candidate will have strong machine learning background and a desire to push the envelope in one or more of the above areas. The ideal candidate would also have hands-on experiences in building Generative AI solutions with LLMs, enjoy operating in dynamic environments, be self-motivated to take on challenging problems to deliver big customer impact, moving fast to ship solutions and then iterating on user feedback and interactions. Key job responsibilities As an Applied Scientist, you will leverage your technical expertise and experience to collaborate with other talented applied scientists and engineers to research and develop novel algorithms and modeling techniques to reduce friction and enable natural and contextual conversations. You will analyze, understand and improve user experiences by leveraging Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in artificial intelligence. You will work on core LLM technologies, including Supervised Fine-Tuning (SFT), In-Context Learning (ICL), Learning from Human Feedback (LHF), etc. Your work will directly impact our customers in the form of novel products and services . We are open to hiring candidates to work out of one of the following locations: Bellevue, WA, USA | Boston, MA, USA | Seattle, WA, USA | Sunnyvale, CA, USA
US, CA, Santa Clara
Amazon is looking for world class scientists and engineers to join its AWS AI Labs working within natural language processing. This group is entrusted with developing core data mining, natural language processing, and machine learning solutions for AWS services. At AWS AI Labs you will invent, implement, and deploy state of the art machine learning algorithms and systems. You will build prototypes and explore conceptually large scale natural language processing solutions. You will interact closely with our customers and with the academic community. You will be at the heart of a growing and exciting focus area for AWS and work with other acclaimed engineers and world famous scientists. AWS Utility Computing (UC) provides product innovations — from foundational services such as Amazon’s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS’s services and features apart in the industry. As a member of the UC organization, you’ll support the development and management of Compute, Database, Storage, Internet of Things (Iot), Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for their cloud services. About the team Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Mentorship & Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. Hybrid Work We value innovation and recognize this sometimes requires uninterrupted time to focus on a build. We also value in-person collaboration and time spent face-to-face. Our team affords employees options to work in the office every day or in a flexible, hybrid work model near one of our U.S. Amazon offices. We are open to hiring candidates to work out of one of the following locations: Santa Clara, CA, USA
US, WA, Seattle
Amazon Web Services (AWS) is building a world-class marketing organization, and we are looking for an experienced Applied Scientist to join the central data and science organization for AWS Marketing. You will lead AWS Measurement, targeting, recommendation, forecasting related AI/ML products and initiatives, and own mechanisms to raise the science and measurement standard. You will work with economists, scientists and engineers within the team, and partner with product and business teams across AWS Marketing to build the next generation marketing measurement, valuation and machine learning capabilities directly leading to improvements in our key performance metrics. A successful candidate has an entrepreneurial spirit and wants to make a big impact on AWS growth. You will develop strong working relationships and thrive in a collaborative team environment. You will work closely with business leaders, scientists, and engineers to translate business and functional requirements into concrete deliverables, including the design, development, testing, and deployment of highly scalable distributed services. The ideal candidate will have experience with machine learning models and causal inference. Additionally, we are seeking candidates with strong rigor in applied sciences and engineering, creativity, curiosity, and great judgment. You will work on high-impact, high-visibility products, with your work improving the experience of AWS leads and customers. AWS Sales, Marketing, and Global Services (SMGS) is responsible for driving revenue, adoption, and growth from the largest and fastest growing small- and mid-market accounts to enterprise-level customers including public sector. The AWS Global Support team interacts with leading companies and believes that world-class support is critical to customer success. AWS Support also partners with a global list of customers that are building mission-critical applications on top of AWS services. Key job responsibilities * Lead the design, development, deployment, and innovation of advanced science models in the strategic area of marketing measurement and optimization. * Partner with scientists, economists, engineers, and product leaders to break down complex business problems into science approaches. * Understand and mine the large amount of data, prototype and implement new learning algorithms and prediction techniques to improve long-term causal estimation approaches. * Design, build, and deploy effective and innovative ML solutions to improve components of our ML and causal inference pipelines. * Publish and present your work at internal and external scientific venues in the fields of ML and causal inference. * Influence long-term science initiatives and mentor other scientists across AWS. 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. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Mentorship & Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. Hybrid Work We value innovation and recognize this sometimes requires uninterrupted time to focus on a build. We also value in-person collaboration and time spent face-to-face. Our team affords employees options to work in the office every day or in a flexible, hybrid work model near one of our U.S. Amazon offices. We are open to hiring candidates to work out of one of the following locations: Arlington, VA, USA | Austin, TX, USA | New York City, NY, USA | Seattle, WA, USA