3Q: Making silicon-vacancy centers practical for quantum networking

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

Quantum networking is a technology that promises to enable tamper-proof communication over optical networks. Synthetic-diamond chips with so-called silicon-vacancy centers are a promising technology for quantum networking because they’re natural light emitters, and they’re small, solid state, and relatively easy to manufacture at scale. But they’ve had one severe drawback, which is that they tend to emit light at a range of different frequencies, which makes exchanging quantum information difficult.

Last year, members of Amazon’s AWS Center for Quantum Computing, together with colleagues at Harvard University, the University of Hamburg, the Hamburg Centre for Ultrafast Imaging, and the Hebrew University of Jerusalem, demonstrated a technique that promises to overcome that drawback. They will present their results in a forthcoming paper in Physical Review Letters titled “Optical entanglement of distinguishable quantum emitters”.

The first author on the paper, David Levonian, a graduate student at Harvard and a quantum research scientist at Amazon, answered three questions about the research for Amazon Science.

Q: What is quantum networking?

David Levonian: A quantum network is a technology that allows you to send quantum bits over fiber optics using single photons — single particles of light. The original interest in it is that by sending these quantum bits between users, you can generate cryptographic keys in a way that's secure. 

As you're able to get higher bandwidth and throughput through these things, you can do really cool stuff. Say Amazon, for example, has a quantum computer, and you don't have one, and you'd like to run computations on Amazon’s, but you don't want to reveal what data you're actually using or what programs you're running. 

It turns out that if your computer can connect to a quantum network, without much special hardware on your side, you can actually send programs and data and have Amazon execute them and then come back to you with a guarantee that nobody looked at any of the stuff that you were doing.

People are trying to build these networks in a variety of ways. What we work on specifically is a hardware implementation that's built on these little chips of diamond. The diamond is made of a bunch of carbon atoms. Pluck out two of those and add a silicon atom. Now there are two holes in the crystal, and the silicon sits in between the two holes. It brings an extra electron, and that electron can absorb light, and it can also store quantum information.

You can use these silicon-vacancy centers as storage registers — people call them quantum memories — to catch light and route it and do quantum operations on it. And you need that quantum memory to build the quantum network for these security applications. People also use trapped atoms or ions and other stuff, but for those you need really big machines. Our system is a little chip, which is pretty cool. 

Q: What problem does your new research solve?

DL: One of the current problems with silicon-vacancy centers is that they're not as uniform as other quantum network hardware that people use. If you have a big network of these things, you want them to communicate between each other with light. And one of the things about silicon-vacancy centers — and actually most of the defect centers in crystals — is that one silicon atom doesn't always emit the same wavelength of light that another defect can receive, so you have trouble matching up your different bits. And that's been a big barrier to actually building these things.

What we came up with is a way of making silicon vacancies that emit light at different wavelengths talk to each other. It’s based on a thought experiment from the ’90s called a Elitzur–Vaidman bomb tester. The motivating idea is that there might be a bomb somewhere, and it's so sensitive that even if you hit it with a single particle of light, it's going to go off. So you want to test whether or not it's there without hitting it with any light at all. 

It turns out there's a quantum-mechanical way to check whether there's a thing blocking light at a position without having any light interact with it, which is pretty unbelievable. But I can give you an idea of how it works. 

There's this device for light called an interferometer. You take a laser beam, you split it into two paths, and then you recombine it at a later point. And where it recombines, you put a beam splitter — a half-transparent mirror that sometimes lets light through and sometimes reflects it 90 degrees. 

So there are two directions light can come out. But if the two paths are the same length, then when the beams get to the beam splitter, they cancel each other out in one direction, and they only come out in the other direction.

Beam splitter interference.png

The weird quantum-mechanical part about this is, even if my laser is only sending a single photon at a time — so there's just one particle of light at a time — those particles still behave the same way. They can split and then interfere with themselves, even though there's only one photon at a time.

So if you send a single photon in, and that photon comes out the port where it wasn't supposed to, I know that one of the paths of the interferometer is blocked. I'm able to detect that there was something blocking one of the paths without having my photon actually run into it. 

SiV experimental setup.png
In the researchers' variation of the Elitzur–Vaidman bomb tester, if a photon reaches the detector, it conveys information about the quantum state of one silicon-vacancy qubit (SiV B), even though it interacted only with the other qubit (SiV A).

We basically we do that, except instead of having the light take two different paths, we split it in frequency. So you can build an interferometer where instead of traveling two paths, the light turns into two different frequencies, and then it gets recombined at a central one. 

Q: How does that help you do secure communication?

DL: There are two vacancy centers, and based on their state they're going to be blocking light or letting light through. You send light in at those two frequencies, and then you combine it. 

If both vacancies are letting light through, then the two paths interfere, and no light comes out at the combined frequency. And if both vacancies are blocking light, no light comes out at the combined frequency. But if one is letting light through, and one is blocking it, then light does come out at that central frequency. 

So if you get light at that combined frequency, you know one was blocking and one wasn't blocking — but you don't know which one is which. And that process generates quantum entanglement between the two vacancies. You can now use one to talk to you and another one to talk to me.

For single quantum bits, if you measure them, you usually change them. So if there's some eavesdropper, they're going to change the bits that I'm sending to you. You can say, ‘Hey, here's the statistics on my information, here’s the statistics on your information.’ If the party in between is adversarial — if they're breaking the rules and just looking at our information and then computing stuff — they're not going to be able to push this statistic above a certain threshold. So as long as that number is higher than the threshold, we know they're not cheating, and our information is secure.

Research areas

Related content

GB, London
Amazon Advertising is looking for a Data Scientist to join its brand new 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 traffic quality prediction (robot and fraud detection), Security forensics and research, Viewability prediction, Brand Safety, Contextual data processing and classification. 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 Data Scientist to work on data science initiatives for contextual data processing and classification that power our contextual advertising solutions. Are you an experienced user of sophisticated analytical techniques that can be applied to answer business questions and chart a sustainable vision? Are you exited by the prospect of communicating insights and recommendations to audiences of varying levels of technical sophistication? Above all, are you an innovator at heart and have a track record of resolving ambiguity to deliver result? As a data scientist, you help our data science team build cutting edge models and measurement 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, define metrics, conceptualize and build algorithms and collaborate with multiple cross-functional teams. Key job responsibilities * Define a long-term science vision for contextual-classification tech, driven fundamentally from the needs of our advertisers and publishers, translating that direction into specific plans for the science team. Interpret complex and interrelated data points and anecdotes to build and communicate this vision. * Collaborate with software engineering teams to Identify and implement elegant statistical and machine learning solutions * Oversee the design, development, and implementation of production level code that handles billions of ad requests. Own the full development cycle: idea, design, prototype, impact assessment, A/B testing (including interpretation of results) and production deployment. * 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
JP, 13, Tokyo
We are seeking a Principal Economist to be the science leader in Amazon's customer growth and engagement. The wide remit covers Prime, delivery experiences, loyalty program (Amazon Points), and marketing. We look forward to partnering with you to advance our innovation on customers’ behalf. Amazon has a trailblazing track record of working with Ph.D. economists in the tech industry and offers a unique environment for economists to thrive. As an economist at Amazon, you will apply the frontier of econometric and economic methods to Amazon’s terabytes of data and intriguing customer problems. Your expertise in building reduced-form or structural causal inference models is exemplary in Amazon. Your strategic thinking in designing mechanisms and products influences how Amazon evolves. In this role, you will build ground-breaking, state-of-the-art econometric models to guide multi-billion-dollar investment decisions around the global Amazon marketplaces. You will own, execute, and expand a research roadmap that connects science, business, and engineering and contributes to Amazon's long term success. As one of the first economists outside North America/EU, you will make an outsized impact to our international marketplaces and pioneer in expanding Amazon’s economist community in Asia. The ideal candidate will be an experienced economist in empirical industrial organization, labour economics, or related structural/reduced-form causal inference fields. You are a self-starter who enjoys ambiguity in a fast-paced and ever-changing environment. You think big on the next game-changing opportunity but also dive deep into every detail that matters. You insist on the highest standards and are consistent in delivering results. Key job responsibilities - Work with Product, Finance, Data Science, and Data Engineering teams across the globe to deliver data-driven insights and products for regional and world-wide launches. - Innovate on how Amazon can leverage data analytics to better serve our customers through selection and pricing. - Contribute to building a strong data science community in Amazon Asia. We are open to hiring candidates to work out of one of the following locations: Tokyo, 13, JPN
DE, BE, Berlin
Ops Integration: Concessions team is looking for a motivated, creative and customer obsessed Snr. Applied Scientist with a strong machine learning background, to develop advanced analytics models (Computer Vision, LLMs, etc.) that improve customer experiences We are the voice of the customer in Amazon’s operations, and we take that role very seriously. If you join this team, you will be a key contributor to delivering the Factory of the Future: leveraging Internet of Things (IoT) and advanced analytics to drive tangible, operational change on the ground. You will collaborate with a wide range of stakeholders (You will partner with Research and Applied Scientists, SDEs, Technical Program Managers, Product Managers and Business Leaders) across the business to develop and refine new ways of assessing challenges within Amazon operations. This role will combine Amazon’s oldest Leadership Principle, with the latest analytical innovations, to deliver business change at scale and efficiently The ideal candidate will have deep and broad experience with theoretical approaches and practical implementations of vision techniques for task automation. They will be a motivated self-starter who can thrive in a fast-paced environment. They will be passionate about staying current with sensing technologies and algorithms in the broader machine vision industry. They will enjoy working in a multi-disciplinary team of engineers, scientists and business leaders. They will seek to understand processes behind data so their recommendations are grounded. Key job responsibilities Your solutions will drive new system capabilities with global impact. You will design highly scalable, large enterprise software solutions involving computer vision. You will develop complex perception algorithms integrating across multiple sensing devices. You will develop metrics to quantify the benefits of a solution and influence project resources. You will validate system performance and use insights from your live models to drive the next generation of model development. Common tasks include: • Research, design, implement and evaluate complex perception and decision making algorithms integrating across multiple disciplines • Work closely with software engineering teams to drive scalable, real-time implementations • Collaborate closely with team members on developing systems from prototyping to production level • Collaborate with teams spread all over the world • Track general business activity and provide clear, compelling management reports on a regular basis We are open to hiring candidates to work out of one of the following locations: Berlin, BE, DEU | Berlin, DEU
DE, BY, Munich
Ops Integration: Concessions team is looking for a motivated, creative and customer obsessed Snr. Applied Scientist with a strong machine learning background, to develop advanced analytics models (Computer Vision, LLMs, etc.) that improve customer experiences We are the voice of the customer in Amazon’s operations, and we take that role very seriously. If you join this team, you will be a key contributor to delivering the Factory of the Future: leveraging Internet of Things (IoT) and advanced analytics to drive tangible, operational change on the ground. You will collaborate with a wide range of stakeholders (You will partner with Research and Applied Scientists, SDEs, Technical Program Managers, Product Managers and Business Leaders) across the business to develop and refine new ways of assessing challenges within Amazon operations. This role will combine Amazon’s oldest Leadership Principle, with the latest analytical innovations, to deliver business change at scale and efficiently The ideal candidate will have deep and broad experience with theoretical approaches and practical implementations of vision techniques for task automation. They will be a motivated self-starter who can thrive in a fast-paced environment. They will be passionate about staying current with sensing technologies and algorithms in the broader machine vision industry. They will enjoy working in a multi-disciplinary team of engineers, scientists and business leaders. They will seek to understand processes behind data so their recommendations are grounded. Key job responsibilities Your solutions will drive new system capabilities with global impact. You will design highly scalable, large enterprise software solutions involving computer vision. You will develop complex perception algorithms integrating across multiple sensing devices. You will develop metrics to quantify the benefits of a solution and influence project resources. You will validate system performance and use insights from your live models to drive the next generation of model development. Common tasks include: • Research, design, implement and evaluate complex perception and decision making algorithms integrating across multiple disciplines • Work closely with software engineering teams to drive scalable, real-time implementations • Collaborate closely with team members on developing systems from prototyping to production level • Collaborate with teams spread all over the world • Track general business activity and provide clear, compelling management reports on a regular basis We are open to hiring candidates to work out of one of the following locations: Munich, BE, DEU | Munich, BY, DEU | Munich, DEU
IT, MI, Milan
Ops Integration: Concessions team is looking for a motivated, creative and customer obsessed Snr. Applied Scientist with a strong machine learning background, to develop advanced analytics models (Computer Vision, LLMs, etc.) that improve customer experiences We are the voice of the customer in Amazon’s operations, and we take that role very seriously. If you join this team, you will be a key contributor to delivering the Factory of the Future: leveraging Internet of Things (IoT) and advanced analytics to drive tangible, operational change on the ground. You will collaborate with a wide range of stakeholders (You will partner with Research and Applied Scientists, SDEs, Technical Program Managers, Product Managers and Business Leaders) across the business to develop and refine new ways of assessing challenges within Amazon operations. This role will combine Amazon’s oldest Leadership Principle, with the latest analytical innovations, to deliver business change at scale and efficiently The ideal candidate will have deep and broad experience with theoretical approaches and practical implementations of vision techniques for task automation. They will be a motivated self-starter who can thrive in a fast-paced environment. They will be passionate about staying current with sensing technologies and algorithms in the broader machine vision industry. They will enjoy working in a multi-disciplinary team of engineers, scientists and business leaders. They will seek to understand processes behind data so their recommendations are grounded. Key job responsibilities Your solutions will drive new system capabilities with global impact. You will design highly scalable, large enterprise software solutions involving computer vision. You will develop complex perception algorithms integrating across multiple sensing devices. You will develop metrics to quantify the benefits of a solution and influence project resources. You will validate system performance and use insights from your live models to drive the next generation of model development. Common tasks include: • Research, design, implement and evaluate complex perception and decision making algorithms integrating across multiple disciplines • Work closely with software engineering teams to drive scalable, real-time implementations • Collaborate closely with team members on developing systems from prototyping to production level • Collaborate with teams spread all over the world • Track general business activity and provide clear, compelling management reports on a regular basis We are open to hiring candidates to work out of one of the following locations: Milan, MI, ITA
ES, M, Madrid
Ops Integration: Concessions team is looking for a motivated, creative and customer obsessed Snr. Applied Scientist with a strong machine learning background, to develop advanced analytics models (Computer Vision, LLMs, etc.) that improve customer experiences We are the voice of the customer in Amazon’s operations, and we take that role very seriously. If you join this team, you will be a key contributor to delivering the Factory of the Future: leveraging Internet of Things (IoT) and advanced analytics to drive tangible, operational change on the ground. You will collaborate with a wide range of stakeholders (You will partner with Research and Applied Scientists, SDEs, Technical Program Managers, Product Managers and Business Leaders) across the business to develop and refine new ways of assessing challenges within Amazon operations. This role will combine Amazon’s oldest Leadership Principle, with the latest analytical innovations, to deliver business change at scale and efficiently The ideal candidate will have deep and broad experience with theoretical approaches and practical implementations of vision techniques for task automation. They will be a motivated self-starter who can thrive in a fast-paced environment. They will be passionate about staying current with sensing technologies and algorithms in the broader machine vision industry. They will enjoy working in a multi-disciplinary team of engineers, scientists and business leaders. They will seek to understand processes behind data so their recommendations are grounded. Key job responsibilities Your solutions will drive new system capabilities with global impact. You will design highly scalable, large enterprise software solutions involving computer vision. You will develop complex perception algorithms integrating across multiple sensing devices. You will develop metrics to quantify the benefits of a solution and influence project resources. You will validate system performance and use insights from your live models to drive the next generation of model development. Common tasks include: • Research, design, implement and evaluate complex perception and decision making algorithms integrating across multiple disciplines • Work closely with software engineering teams to drive scalable, real-time implementations • Collaborate closely with team members on developing systems from prototyping to production level • Collaborate with teams spread all over the world • Track general business activity and provide clear, compelling management reports on a regular basis We are open to hiring candidates to work out of one of the following locations: Madrid, ESP | Madrid, M, ESP
US, TX, Austin
The role is available Arlington, Virginia (may consider New York, NY, Los Angeles, CA, or Toronto, Canada). Calling all inventors to work on exciting new opportunities in Sponsored Products. Amazon is building a world class advertising business and defining and delivering a collection of self-service performance advertising products that drive discovery and sales of merchandise. Our products are strategically important to our Retail and Marketplace businesses, driving long-term growth. Sponsored Products (SP) helps merchants, retail vendors, and brand owners grows incremental sales of their products sold on Amazon through native advertising. SP achieves this by using a combination of machine learning, big data analytics, ultra-low latency high-volume engineering systems, and quantitative product focus. We are a highly motivated, collaborative and fun-loving group with an entrepreneurial spirit and bias for action. You will join a newly-founded team with a broad mandate to experiment and innovate, which gives us the flexibility to explore and apply scientific techniques to novel product problems. You will have the satisfaction of seeing your work improve the experience of millions of Amazon shoppers while driving quantifiable revenue impact. More importantly, you will have the opportunity to broaden your technical skills, work with Generative AI, and be a science leader in an environment that thrives on creativity, experimentation, and product innovation. We are open to hiring candidates to work out of one of the following locations: Austin, TX, USA
GB, London
Ops Integration: Concessions team is looking for a motivated, creative and customer obsessed Snr. Applied Scientist with a strong machine learning background, to develop advanced analytics models (Computer Vision, LLMs, etc.) that improve customer experiences We are the voice of the customer in Amazon’s operations, and we take that role very seriously. If you join this team, you will be a key contributor to delivering the Factory of the Future: leveraging Internet of Things (IoT) and advanced analytics to drive tangible, operational change on the ground. You will collaborate with a wide range of stakeholders (You will partner with Research and Applied Scientists, SDEs, Technical Program Managers, Product Managers and Business Leaders) across the business to develop and refine new ways of assessing challenges within Amazon operations. This role will combine Amazon’s oldest Leadership Principle, with the latest analytical innovations, to deliver business change at scale and efficiently The ideal candidate will have deep and broad experience with theoretical approaches and practical implementations of vision techniques for task automation. They will be a motivated self-starter who can thrive in a fast-paced environment. They will be passionate about staying current with sensing technologies and algorithms in the broader machine vision industry. They will enjoy working in a multi-disciplinary team of engineers, scientists and business leaders. They will seek to understand processes behind data so their recommendations are grounded. Key job responsibilities Your solutions will drive new system capabilities with global impact. You will design highly scalable, large enterprise software solutions involving computer vision. You will develop complex perception algorithms integrating across multiple sensing devices. You will develop metrics to quantify the benefits of a solution and influence project resources. You will validate system performance and use insights from your live models to drive the next generation of model development. Common tasks include: • Research, design, implement and evaluate complex perception and decision making algorithms integrating across multiple disciplines • Work closely with software engineering teams to drive scalable, real-time implementations • Collaborate closely with team members on developing systems from prototyping to production level • Collaborate with teams spread all over the world • Track general business activity and provide clear, compelling management reports on a regular basis Basic Qualifications -Masters in Computer Science, Machine Learning, Robotics or equivalent with a focus on Computer Vision. -2+ years of experience of building machine learning models for business application -Broad knowledge of fundamentals and state of the art in computer vision and machine learning -Strong coding skills in two or more programming languages such as Python or C/C++ -Knowledge of fundamentals in optimization, supervised and reinforcement learning -Excellent problem-solving ability Preferred Qualifications -PhD and 4+ years of industry or academic applied research experience applying Computer Vision techniques and developing Computer vision algorithms -Depth and breadth in state-of-the-art computer vision and machine learning technologies and experience designing and building computer vision solutions -Industry experience in sensor systems and the development of production computer vision and machine learning applications built to use them -Experience developing software interfacing to AWS services -Excellent written and verbal communication skills with the ability to present complex technical information in a clear and concise manner to a variety of audiences -Ability to work on a diverse team or with a diverse range of coworkers -Experience in publishing at major Computer Vision, ML or Robotics conferences or Journals (CVPR, ICCV, ECCV, NeurIPS, ICML, IJCV, ICRA, IROS, RSS,...) We are open to hiring candidates to work out of one of the following locations: London, GBR
US, WA, Seattle
Want to work in a start-up environment with the resources of Amazon behind you? Do you want to have direct and immediate impact on millions of customers every day? If you are a self-starter, passionate about machine learning, deep learning, big data systems, enjoy designing and implementing new features and machine learned models, and intrigued by ambiguous problems, look no further. Amazon Advertising operates at the intersection of eCommerce and advertising, offering a rich array of digital display advertising solutions with the goal of helping our customers find and discover anything they want to buy. We help advertisers of all types to reach Amazon customers on Amazon.com, across our other owned and operated sites, on other high quality sites across the web, and on millions of Kindles, tablets, and mobile devices. We start with the customer and work backwards in everything we do, including advertising. If you’re interested in joining a rapidly growing team working to build a unique, world-class advertising group with a relentless focus on the customer, you’ve come to the right place. About Our Team: Our team is responsible for building a new advertising product for non-endemic advertisers. We are tasked with taking this start-up offering to market, with the goal of empowering over one million non-endemic advertisers to independently plan and execute campaigns. “Non-endemic” brands offer products and services that are not sold/available in Amazon’s retail marketplace, including restaurants, hotels, airlines, insurance, telecom, and automobiles. We are embarking on a multi-year vision to democratize display advertising for non-endemic advertisers at self-service scale. This will open up Amazon Ads to self-service non-endemic demand— whether they sell on the Amazon store or not— to activate Amazon Ads first-party audiences built from shopping and streaming signals and access unique ad inventory to help grow their business. Open to hire in NYC or Seattle. Key job responsibilities - Drive end-to-end Machine Learning projects that have a high degree of ambiguity, scale, complexity. - Perform hands-on analysis and modeling of enormous data sets to develop insights that increase traffic monetization and merchandise sales, without compromising the shopper experience. - Build machine learning models, perform proof-of-concept, experiment, optimize, and deploy your models into production; work closely with software engineers to assist in productionizing your ML models. - Run A/B experiments, gather data, and perform statistical analysis. - Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving. - Research new and innovative machine learning approaches. - Train and fine-tune neural models including transformers and language models. - Recruit Applied Scientists to the team and provide mentorship. We are open to hiring candidates to work out of one of the following locations: Seattle, WA, USA
LU, Luxembourg
Ops Integration: Concessions team is looking for a motivated, creative and customer obsessed Snr. Applied Scientist with a strong machine learning background, to develop advanced analytics models (Computer Vision, LLMs, etc.) that improve customer experiences We are the voice of the customer in Amazon’s operations, and we take that role very seriously. If you join this team, you will be a key contributor to delivering the Factory of the Future: leveraging Internet of Things (IoT) and advanced analytics to drive tangible, operational change on the ground. You will collaborate with a wide range of stakeholders (You will partner with Research and Applied Scientists, SDEs, Technical Program Managers, Product Managers and Business Leaders) across the business to develop and refine new ways of assessing challenges within Amazon operations. This role will combine Amazon’s oldest Leadership Principle, with the latest analytical innovations, to deliver business change at scale and efficiently The ideal candidate will have deep and broad experience with theoretical approaches and practical implementations of vision techniques for task automation. They will be a motivated self-starter who can thrive in a fast-paced environment. They will be passionate about staying current with sensing technologies and algorithms in the broader machine vision industry. They will enjoy working in a multi-disciplinary team of engineers, scientists and business leaders. They will seek to understand processes behind data so their recommendations are grounded. Key job responsibilities Your solutions will drive new system capabilities with global impact. You will design highly scalable, large enterprise software solutions involving computer vision. You will develop complex perception algorithms integrating across multiple sensing devices. You will develop metrics to quantify the benefits of a solution and influence project resources. You will validate system performance and use insights from your live models to drive the next generation of model development. Common tasks include: • Research, design, implement and evaluate complex perception and decision making algorithms integrating across multiple disciplines • Work closely with software engineering teams to drive scalable, real-time implementations • Collaborate closely with team members on developing systems from prototyping to production level • Collaborate with teams spread all over the world • Track general business activity and provide clear, compelling management reports on a regular basis We are open to hiring candidates to work out of one of the following locations: Luxembourg, LUX