Antia Lamas-Linares, quantum networking lead at Amazon Web Services and an expert in quantum optics, is seen looking into the camera
Antia Lamas-Linares, quantum networking lead at Amazon Web Services and an expert in quantum optics, was among the ‘first wave’ of scientists to gain a PhD in quantum technology.

Antia Lamas-Linares’s path into the world of quantum

Among the ‘first wave’ of scientists to gain a PhD in quantum technology, the senior manager of research science discusses her two-decade-long career journey.

In January 2021, Antia Lamas-Linares joined Amazon Web Services (AWS) to work on quantum technologies.

A quantum information scientist, Lamas-Linares is an expert in quantum optics. More precisely, in photonic (optical) implementations of quantum-information protocols. Her career to date includes pioneering research on quantum key distribution — formerly known as quantum cryptography — superconducting single-photon detectors and space-based quantum technology (including several patents), in addition to high-performance computing.

Related content
Researchers affiliated with Amazon Web Services' Center for Quantum Computing are presenting their work this week at the Conference on Quantum Information Processing.

Quantum science and technologies are evolving fast, and for the first time, small prototype quantum computers are appearing around the world. Indeed, the Amazon Braket service provides access to these computers for researchers and institutions. AWS itself announced the opening of its Center for Quantum Computing in October 2021. While quantum processors already exhibit some interesting quantum mechanical behaviors, they have some way to go before they outperform “classical” computers in truly disruptive ways.

Quantum computers work through the manipulation of quantum bits, known as qubits, instead of conventional digital bits. Lamas-Linares joined AWS to focus on research related to connecting quantum devices with each other.

“You can think of quantum computing as dealing with stationary qubits and quantum networking as dealing with ‘flying qubits’ – qubits going from A to B,” says Lamas-Linares.

Quantum networking

To understand the coming importance of quantum networking, first consider a central disruption that quantum computers are ultimately expected to deliver: a potential, future threat to modern digital security. That is because quantum computers have the potential to outperform classical computers, including the ability to break encryption methods currently relied on for modern communications and data security.

The center's mission is to address fundamental scientific and engineering challenges and to develop new hardware, software, and applications for quantum networks.

“This once-remote threat of a hypothetical quantum computer breaking modern encryption is becoming less of a hypothetical and more of a ‘not if but when’,” says Lamas-Linares.

One potential solution to this challenge would be go “full quantum” in how information is protected in the first place, says Lamas-Linares, using quantum encryption keys.

“One of the main applications — and low-hanging fruit — of quantum networking is the ability to distribute those keys securely. This involves exploiting the inherent randomness and correlations that exist in quantum systems to create perfectly secure correlated numbers that can then be used for cryptography.”

In short, quantum networking has the potential to also deliver perfect privacy. It would be easy to fall down a quantum rabbit hole here. Suffice it to say, quantum entanglement — a fundamental quantum phenomenon — can be exploited to distribute these keys in such a way that no intermediary company involved in the warehousing or transmitting of data would be able to access that data.

The challenge and promise of quantum computing | Amazon Science

Only the possessor of the quantum keys — the data owners — can decrypt and access that data. In the future, such perfect protection of customer data will be crucial to every organization, from financial institutions and governments to hospitals and industry. The goal of quantum key distribution is to securely transmit those keys to where they need to be.

“At AWS we often say that security is job zero — more important than any other priority. That’s because if customers don't trust the cloud, then most business models just won’t work in the cloud. Customers need confidence that their data and transactions are secure,” says Lamas-Linares.

Mathematical games

The first quantum cryptography protocol, theoretical but provably secure, was called BB84 and published in 1984. At the time, a young Lamas-Linares was growing up in Santiago, Spain, busily getting hooked on mathematics and physics: she did not yet speak English, but recalls her parents owned the Spanish translation of a collection of classic “Mathematical Games” columns from Scientific American, written by Martin Gardner.

“That really caught my attention — I was fascinated,” says Lamas-Linares. Later, in 1988, Stephen Hawking’s “The Brief History of Time” further captivated her. “It’s kind of a cliché, but that book set me on my path.”

Related content
New method enables entanglement between vacancy centers tuned to different wavelengths of light.

It was a path that took Lamas-Linares to study physics at the University of Santiago de Compostela. After graduating, Lamas-Linares moved for a year to the University of Sheffield, UK, via the European Union’s Erasmus student exchange program, before spending a year completing a master’s in applied optics at Imperial College London.

Why the focus on optics?

[Optics] is one of these fields in physics where you can literally see the things that are happening. If you study optics from a mathematical point of view, it’ll tell you something that you can recreate perfectly with light and lenses.
Antia Lamas-Linares

“It’s one of these fields in physics where you can literally see the things that are happening. If you study optics from a mathematical point of view, it’ll tell you something that you can recreate perfectly with light and lenses. I thought that was really cool,” she said.

Then Lamas-Linares started learning about quantum optics, and so-called “squeezed states” of light. Being quantum, and therefore tiny, this is physics you cannot see with your eyes, but she thought it was cooler still. In 2003, Lamas-Linares completed her doctorate in physics at the University of Oxford.

Lamas-Linares’s subsequent career has continued an international trend. Highlights include becoming an assistant professor at the National University of Singapore (NUS), where she soon set up a new quantum optics lab and became principal investigator at the university’s Centre for Quantum Technologies. She later became a senior research fellow at the US National Institute of Standards and Technology in Boulder, Colorado, and a research associate doing high performance computing at the Texas Advanced Computing Center in Austin.

Moving into industry

When Lamas-Linares made the move from academia to industry, it was to join an NUS spinout company, SpeQtral, as chief quantum scientist in 2019. The switch resulted from an itch for her work to have more direct real-world impact.

“Academia is full of what we call hero experiments, where you make something work once, but maybe afterward it self-destructs or melts or something; the important thing is you showed something was possible; a viable effect. That’s great, but it’s nowhere near what you need to create a useful technology,” says Lamas-Linares. “First and foremost, I'm an experimentalist — I build devices. And I wanted to build robust versions of useful technology. That sort of engineering challenge doesn’t make sense for academia — you have to go to industry. I want to bring quantum technologies to the point where it is the ‘best’ solution to a technical problem and so it becomes part of the standard toolbox.”

Women in Quantum Summit - Antia Lamas Linares

SpeQtral pioneers the development of miniaturized sources of quantum-entangled photons, designed to be deployed on satellites as a means to distribute quantum keys around the Earth. The company has successfully demonstrated such miniaturized technology in space, using its shoebox sized “cubesat”, SpooQy-1.

“SpeQtral had already put an entanglement source in space when I joined as chief quantum scientist,” Lamas-Linares recalls. “By this time I’d been working in the field for two decades, having done a lot of work on entanglement sources, but also on whole systems designed to implement quantum key distribution systems over free space, and in hacking those same systems to show which parts needed further thought.”

While at SpeQtral, industry networking meant Lamas-Linares talked with Amazon about this technology. “That’s how I became more aware of what that Amazon was doing things in quantum technologies,” says Lamas-Linares. “It turned out that one of my former colleagues, Simone Severini, was working at AWS in quantum computing. One day he said to me: ‘Hey, we're doing really interesting stuff. Would you be interested in joining us?’.”

What was it that Severini saw in Lamas-Linares?

“I’ve known Antia professionally for about 20 years, and have always been struck by her adaptability and the fact that she is a real ‘owner’,” he says. “Ownership is fundamental in a complex, pioneering environment like this. Nobody is telling you exactly what to do — you have to find your own way, and push when you find friction. “Antia fits Amazon very well — she has a strong bias for action.”

Amazon’s appeal

For Lamas-Linares’s part, she was attracted to Amazon’s resources, capability, and very long-term vision.

“Amazon is only interested in building things that have a clear application and benefit for their customers, but if they are convinced of that customer value, they will invest for as many years as necessary to reach the required level of technological readiness,” she explained. “That’s exciting, and it’s much harder to do in the start-up/venture capitalist environment, particularly with complicated hardware products.”

Related content
New phase estimation technique reduces qubit count, while learning framework enables characterization of noisy quantum systems.

One of the main challenges in making strides in quantum networking, says Lamas-Linares, is technological integration.

“Whatever quantum technology you develop, before it can be of any use to your customers, an entire ecosystem of additional technology needs to be built up around it, and the people needed to do that barely exist for quantum technologies. Finding that combination of expertise and building the required tools is a non-trivial challenge.”

As quantum technologies are taken up by industry, we’re starting to make the molds for what quantum engineers will be. That, to me, is really exciting.
Antia Lamas-Linares

The sheer newness of many quantum technologies makes it tricky to orchestrate a successful career in the field. Does Lamas-Linares, herself in the first wave of scientists to gain a PhD in quantum technology, have any advice to offer?

“I am definitively not qualified to give anyone advice, but I would say this: Don’t be afraid to take an unconventional path. Especially in emerging fields like this, you just don’t know what the right combination of skills and experience will turn out to be.”

Lamas-Linares points out that “quantum engineers” don’t really exist as yet.

“Engineers take established knowledge and they perfect it. As quantum technologies are taken up by industry, we’re starting to make the molds for what quantum engineers will be. That, to me, is really exciting.”

Related content

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
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
GB, Cambridge
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: Cambridge, GBR | London, GBR
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, 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
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
IN, KA, Bangalore
Alexa is the voice activated digital assistant powering devices like Amazon Echo, Echo Dot, Echo Show, and Fire TV, which are at the forefront of this latest technology wave. To preserve our customers’ experience and trust, the Alexa Sensitive Content Intelligence (ASCI) team creates policies and builds services and tools through Machine Learning techniques to detect and mitigate sensitive content across Alexa. We are looking for an experienced Senior Applied Scientist to build industry-leading technologies in attribute extraction and sensitive content detection across all languages and countries. A Senior Applied Scientist will be a tech lead for a team of exceptional scientists to develop novel algorithms and modeling techniques to advance the state of the art in NLP or CV related tasks. You will work in a hybrid, fast-paced organization where scientists, engineers, and product managers work together to build customer facing experiences. You will collaborate with and mentor other scientists to raise the bar of scientific research in Amazon. Your work will directly impact our customers in the form of products and services that make use of speech, language, and computer vision technologies. We are looking for a leader with strong technical experiences a passion for building scientific driven solutions in a fast-paced environment. You should have good understanding of NLP models (e.g. LSTM, transformer based models) or CV models (e.g. CNN, AlexNet, ResNet) and where to apply them in different business cases. You leverage your exceptional technical expertise, a sound understanding of the fundamentals of Computer Science, and practical experience of building large-scale distributed systems to creating reliable, scalable, and high-performance products. In addition to technical depth, you must possess exceptional communication skills and understand how to influence key stakeholders. You will be joining a select group of people making history producing one of the most highly rated products in Amazon's history, so if you are looking for a challenging and innovative role where you can solve important problems while growing as a leader, this may be the place for you. Key job responsibilities You'll lead the science solution design, run experiments, research new algorithms, and find new ways of optimizing customer experience. You set examples for the team on good science practice and standards. Besides theoretical analysis and innovation, you will work closely with talented engineers and ML scientists to put your algorithms and models into practice. Your work will directly impact the trust customers place in Alexa, globally. You contribute directly to our growth by hiring smart and motivated Scientists to establish teams that can deliver swiftly and predictably, adjusting in an agile fashion to deliver what our customers need. A day in the life You will be working with a group of talented scientists on researching algorithm and running experiments to test scientific proposal/solutions to improve our sensitive contents detection and mitigation. This will involve collaboration with partner teams including engineering, PMs, data annotators, and other scientists to discuss data quality, policy, and model development. You will mentor other scientists, review and guide their work, help develop roadmaps for the team. You work closely with partner teams across Alexa to deliver platform features that require cross-team leadership. About the hiring group About the team The mission of the Alexa Sensitive Content Intelligence (ASCI) team is to (1) minimize negative surprises to customers caused by sensitive content, (2) detect and prevent potential brand-damaging interactions, and (3) build customer trust through appropriate interactions on sensitive topics. The term “sensitive content” includes within its scope a wide range of categories of content such as offensive content (e.g., hate speech, racist speech), profanity, content that is suitable only for certain age groups, politically polarizing content, and religiously polarizing content. The term “content” refers to any material that is exposed to customers by Alexa (including both 1P and 3P experiences) and includes text, speech, audio, and video. We are open to hiring candidates to work out of one of the following locations: Bangalore, KA, IND
IN, KA, Bangalore
Alexa is the voice activated digital assistant powering devices like Amazon Echo, Echo Dot, Echo Show, and Fire TV, which are at the forefront of this latest technology wave. To preserve our customers’ experience and trust, the Alexa Sensitive Content Intelligence (ASCI) team creates policies and builds services and tools through Machine Learning techniques to detect and mitigate sensitive content across Alexa. We are looking for an experienced Applied Scientist to build industry-leading technologies in attribute extraction and sensitive content detection across all languages and countries. An Applied Scientist will be working with a team of exceptional scientists to develop novel algorithms and modeling techniques to advance the state of the art in NLP or CV related tasks. You will work in a hybrid, fast-paced organization where scientists, engineers, and product managers work together to build customer facing experiences. You will collaborate with and mentor other scientists to raise the bar of scientific research in Amazon. Your work will directly impact our customers in the form of products and services that make use of speech, language, and computer vision technologies. We are looking for a leader with strong technical experiences a passion for building scientific driven solutions in a fast-paced environment. You should have good understanding of NLP models (e.g. LSTM, transformer based models) or CV models (e.g. CNN, AlexNet, ResNet) and where to apply them in different business cases. You leverage your exceptional technical expertise, a sound understanding of the fundamentals of Computer Science, and practical experience of building large-scale distributed systems to creating reliable, scalable, and high-performance products. In addition to technical depth, you must possess exceptional communication skills and understand how to influence key stakeholders. You will be joining a select group of people making history producing one of the most highly rated products in Amazon's history, so if you are looking for a challenging and innovative role where you can solve important problems while growing as a leader, this may be the place for you. Key job responsibilities You'll participate the science solution design, run experiments, research new algorithms, and find new ways of optimizing customer experience. You set examples for the team on good science practice and standards. Besides theoretical analysis and innovation, you will work closely with talented engineers and ML scientists to put your algorithms and models into practice. Your work will directly impact the trust customers place in Alexa, globally. You contribute directly to our growth by hiring smart and motivated Scientists to establish teams that can deliver swiftly and predictably, adjusting in an agile fashion to deliver what our customers need. A day in the life You will be working with a group of talented scientists on researching algorithm and running experiments to test scientific proposal/solutions to improve our sensitive contents detection and mitigation. This will involve collaboration with partner teams including engineering, PMs, data annotators, and other scientists to discuss data quality, policy, and model development. You will mentor other scientists, review and guide their work, help develop roadmaps for the team. You work closely with partner teams across Alexa to deliver platform features that require cross-team leadership. About the hiring group About the team The mission of the Alexa Sensitive Content Intelligence (ASCI) team is to (1) minimize negative surprises to customers caused by sensitive content, (2) detect and prevent potential brand-damaging interactions, and (3) build customer trust through appropriate interactions on sensitive topics. The term “sensitive content” includes within its scope a wide range of categories of content such as offensive content (e.g., hate speech, racist speech), profanity, content that is suitable only for certain age groups, politically polarizing content, and religiously polarizing content. The term “content” refers to any material that is exposed to customers by Alexa (including both 1P and 3P experiences) and includes text, speech, audio, and video. We are open to hiring candidates to work out of one of the following locations: Bangalore, KA, IND
US, WA, Seattle
Are you a scientist interested in pushing the state of the art in Generative AI, LLMs, LMMs? Are you interested in working on ground-breaking research projects that will lead to great products and scientific publications? Do you wish you had access to large datasets? Answer yes to any of these questions and you’ll fit right in here at Amazon. We are looking for a hands-on researcher, who wants to derive, implement, and test the next generation of Generative AI algorithms in multiple projects ranging from Computer Vision, ML, and NLP. The research we do is innovative, multidisciplinary, and far-reaching. We aim to define, deploy, and publish cutting edge research. In order to achieve our vision, we think big and tackle technology problems that are cutting edge. Where technology does not exist, we will build it. Where it exists we will need to modify it to make it work at Amazon scale. We need members who are passionate and willing to learn. Key job responsibilities - Derive novel computer vision, machine learning, and NLP algorithms. - Define scalable computer vision, machine learning and NLP models. - Invent the next generation of Generative AI models. - Work with large datasets. - Work with software engineering teams to deploy your - Publish your work at top conferences/journals. - Mentor team members. A day in the life We are a team of seasoned scientists. We work on science problems and publish our results at major scientific conferences. We work with multiple other science teams at Amazon. About the team We are a tight-knit group that shares our experiences and help each other succeed. We believe in team work. We love hard problems and like to move fast in a growing and changing environment. We use data to guide our decisions and we always push the technology and process boundaries of what is feasible on behalf of our customers. If that sounds like an environment you like, join us. We are open to hiring candidates to work out of one of the following locations: Seattle, WA, USA