A blue plaque at Kings College in Cambridge commemorating former student and computer pioneer Alan Turing
A blue plaque at Kings College in Cambridge, UK, commemorating former student and computer pioneer Alan Turing.
chrisdorney/Getty Images

Does the Turing Test pass the test of time?

Four Amazon scientists weigh in on whether the famed mathematician's definition of artificial intelligence is still applicable, and what might surprise him most today.

On Oct. 1, 1950, the journal Mind featured a 27-page entry authored by Alan Turing. More than 70 years later, that paper — "Computing Machinery and Intelligence" — which posed the question, “Can machines think?” remains foundational in artificial intelligence.

However, while the paper is iconic, the original goal of building a system comparable to human intelligence has proved elusive. In fact, Alexa VP and Head Scientist Rohit Prasad has written, “I believe the goal put forth by Turing is not a useful one for AI scientists like myself to work toward. The Turing Test is fraught with limitations, some of which Turing himself debated in his seminal paper.”

Clockwise from top left: Yoelle Maarek, vice president of research and science for Alexa Shopping; Alex Smola, AWS vice president and distinguished scientist; Gaurav Sukhatme, the USC Fletcher Jones Foundation Endowed Chair in Computer Science and Computer Engineering and an Amazon Scholar; Nikko Strom, Alexa AI vice president and distinguished scientist.
Clockwise from top left: Yoelle Maarek, vice president of research and science for Alexa Shopping; Alex Smola, AWS vice president and distinguished scientist; Gaurav Sukhatme, the USC Fletcher Jones Foundation Endowed Chair in Computer Science and Computer Engineering and an Amazon Scholar; Nikko Ström, Alexa AI vice president and distinguished scientist.

In light of the 2021 AAAI Conference on Artificial Intelligence, we asked scientists and scholars at Amazon how they view that paper today. We spoke with Yoelle Maarek, vice president of research and science for Alexa Shopping; Alex Smola, AWS vice president and distinguished scientist; Nikko Ström, Alexa AI vice president and distinguished scientist; and Gaurav Sukhatme, the USC Fletcher Jones Foundation Endowed Chair in Computer Science and Computer Engineering and an Amazon Scholar.

We asked them whether Turing’s definition of artificial intelligence still applies, what they think Turing would be surprised by in 2020, and which of today’s problems researchers will still be puzzling over 70 years from now.

Q. Does Turing’s definition of AI (essentially “a test of a machine's ability to exhibit intelligent behavior equivalent to, or indistinguishable from, that of a human”) still apply, or does it need to be updated?

Smola: “The core of the question remains as relevant as it was 70 years ago. That said, I would argue that rather than seeking binary (yes/no) tests for AI we should have something more gradual. For instance, the argument could be about how long a machine can fool a human. Alexa and others by now do a pretty good job for many queries for single turn, and there are even multi-turn systems that are pretty capable. In fact, you can test out some of them as part of the Alexa Prize (‘Alexa, let’s chat’). Using time, you can measure progress more finely, e.g., by the number of minutes (or turns) it takes to uncover the imposter, rather than a fixed time limit.”

Evaluating AI on the basis of being indistinguishable from human intelligence makes as much sense as evaluating airplanes based on being indistinguishable from birds.
Nikko Strom

Maarek: “It is clear it is not a perfect definition. First, I doubt there exists a universally agreed-upon definition of intelligence, and it is not clear what ‘a human’ refers to. Is that any human? Can a machine be indistinguishable from some humans and not from others? It is, however, a simplifier that can still be used for inspiration. And it does bring inspiration, see for instance the outstanding progress in chess or Go. There are, of course, so many other areas where machines still require learning, and these challenges keep inspiring scientists. Two such areas, among others, on which we are focusing in Alexa Shopping Research are to make advancements in conversational shopping (as a subfield of conversational AI) and computational humor. With even small progress in these hard AI challenges, I am sure we will bring tremendous value to our customers and even make them smile.”

Ström: “Evaluating AI on the basis of being indistinguishable from human intelligence makes as much sense as evaluating airplanes based on being indistinguishable from birds. We may never have a single definition, but a common thread is generalizability, i.e., the ability to be successful in novel situations, not considered during the design of the system. To achieve such generalization, an AI needs the ability to reason and plan, have a representation of world-knowledge, an ability to learn and remember, and an ability to regulate and integrate those cognitive capabilities toward goals.

"The AI also needs to be an active participant in the world, and when evaluating intelligence, one needs to consider not just whether goals are met, but how efficiently goals are reached based on efficacy metrics that depend on the application — e.g., cost, energy use, speed, et cetera. My prediction is that once one or several successful such systems exist, a standard model will emerge that becomes a de facto definition of AI.”

Sukhatme: “I think the idea that we want a machine to have the ‘ability to exhibit intelligent behavior equivalent to, or indistinguishable from, that of a human’ still applies when thinking about AI. However, this idea has over the years been interpreted very narrowly when it comes to the ‘test’ – i.e. people look for human-like performance on some narrow task. I think we need to remind people that intelligence is very broad set of capabilities and we need to acknowledge that humans have deep understanding of the world, are social, have empathy, can and do learn continually and can do a very broad range of things. If we are to say that we’ve built a machine or system that exhibits AI, I would want to see it exhibit behavior indistinguishable from humans on a similar breadth of abilities.”

Q. In terms of AI, what do you think would surprise Turing today?

I think he'd be surprised at how far we’ve come in terms of the technological artifacts we’ve produced. And he’d be disappointed in how un-intelligent they are
Gaurav Sukhatme

Sukhatme: “I think he’d be surprised at how far we’ve come in terms of the technological artifacts we’ve produced. And he’d be disappointed in how un-intelligent they are.”

Maarek: “Hard to answer, as this is pure speculation. But I would like to believe that computational humor would be one of them, simply because it makes us all smile.”

Ström: “The resolution of Moravec's paradox. Machine learning and, in particular, deep learning, is now enabling us to solve sensorimotor tasks in robotics, and sensory tasks such as object recognition and speech recognition. Yet general intelligence is still a hard, largely unsolved, problem. I also think Turing would be fascinated by quantum computers.”

Smola: “The thing that would surprise Turing the most is probably the amount of data and its ready availability. The fact that we can build language models on more than 1 trillion characters of text, or that we have hundreds of millions of images available, is probably the biggest differentiator. It’s only thanks to these mountains of data that we’ve been able to build systems that generate speech (e.g. Amazon Polly), that translate text (e.g. Amazon Translate), that recognize speech (e.g. Transcribe), that recognize images, faces in images, or that are able to analyze poses in video.

"At the same time, it’s unclear whether he would have anticipated the exponential growth in computation. The UNIVAC was capable of performing around 4,000 floating point operators (FLOPS) per second. Our latest P4 servers can carry out around 1-2 PetaFLOPS, so that’s 1,000,000,000,000,000 multiply-adds — and you can rent them for around $30 an hour.”

Q. Which of today’s theoretical questions will scientists still be puzzling about in 2090?

Sukhatme: “How do human brains do what they do in such an energy efficient manner? What is consciousness?”

Maarek: “In terms of theoretical computer science problems, I believe that hard AI problems like Winograd Schema Challenge, will be resolved. But I want to believe that other AI challenges, like giving a true sense of humor to machines, won’t be solved yet. It's humbling to think that in 1534 the French writer François Rabelais said, 'le rire est le propre de l’homme' — which can be translated as 'the laugh is unique to humans'. It’s probably why my team is researching computational humor — it’s fun and hard.”

Ström: “In 70 years, I predict that AI has been solved for practical purposes and is used for cognitive tasks, small and large. So that is not it. Some long-standing profound questions like NP=P will still be unsolved. The physics model of time, space, energy and matter will still not be complete, and the question about how life spontaneously emerges from lifeless building-blocks will still puzzle both human and synthetic scientists. Unless we get lucky, 70 years will also not be enough to determine if there is alien intelligent life in our galaxy.”

In the foreground, a welcome to Bletchley Park offers a guide, in the background a group of tourists get a guided tour. This area was used in World War 2 to break the German Enigma Codes.
A group of tourists get a guided tour of the grounds of Bletchley Park. This area was used in World War 2 to break the German Enigma Codes.
NeonJellyfish/Getty Images

Smola: “That’s really difficult since most projections don’t hold up well, even for a decade or so. In 2016, when I interviewed for a job and was deciding between Amazon and another major company, I was told at that other company that I was making a mistake in betting on AI in the cloud. Problems that will keep us awake, probably forever, are how to appropriately balance innovation while also protecting individual liberties. Those challenges will require continuous and careful consideration by multiple stakeholders in academia, industry, government, and our society. Likewise, we will never be able to have a full characterization of the empirical power of our statistical tools. In simple terms, we’ll likely always encounter algorithms that work way better than they should in theory. Lastly, there’s the issue of actually gaining causal understanding from data as to how the world works. This is hard and has been vexing (natural) scientists for centuries.

"Areas where we will likely see a lot of progress include autonomous systems. There’s so much economic promise in self-driving vehicles that I think we will eventually deliver something that works. The algorithms used for cars can also be adapted for a wide variety of other problems such as manufacturing, maintenance, et cetera. The next decade or two will be amazing — and we’ll likely also see great progress on the Turing test itself.”

View from space of a connected network around planet Earth representing the Internet of Things.
Sign up for our newsletter

Research areas

Related content

US, CA, Santa Clara
Job summaryAmazon is looking for a passionate, talented, and inventive Applied Scientist with a strong machine learning background to help build industry-leading language technology.Our mission is to provide a delightful experience to Amazon’s customers by pushing the envelope in Natural Language Processing (NLP), Natural Language Understanding (NLU), Dialog management, conversational AI and Machine Learning (ML).As part of our AI team in Amazon AWS, you will work alongside internationally recognized experts to develop novel algorithms and modeling techniques to advance the state-of-the-art in human language technology. Your work will directly impact millions of our customers in the form of products and services, as well as contributing to the wider research community. You will gain hands on experience with Amazon’s heterogeneous text and structured data sources, and large-scale computing resources to accelerate advances in language understanding.We are hiring primarily in Conversational AI / Dialog System Development areas: NLP, NLU, Dialog Management, NLG.This role can be based in NYC, Seattle or Palo Alto.Inclusive Team CultureHere at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences.Work/Life BalanceOur team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.Mentorship & Career GrowthOur team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future.
US, NY, New York
Job summaryAmazon is looking for a passionate, talented, and inventive Applied Scientist with a strong machine learning background to help build industry-leading language technology.Our mission is to provide a delightful experience to Amazon’s customers by pushing the envelope in Natural Language Processing (NLP), Natural Language Understanding (NLU), Dialog management, conversational AI and Machine Learning (ML).As part of our AI team in Amazon AWS, you will work alongside internationally recognized experts to develop novel algorithms and modeling techniques to advance the state-of-the-art in human language technology. Your work will directly impact millions of our customers in the form of products and services, as well as contributing to the wider research community. You will gain hands on experience with Amazon’s heterogeneous text and structured data sources, and large-scale computing resources to accelerate advances in language understanding.We are hiring primarily in Conversational AI / Dialog System Development areas: NLP, NLU, Dialog Management, NLG.This role can be based in NYC, Seattle or Palo Alto.Inclusive Team CultureHere at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences.Work/Life BalanceOur team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.Mentorship & Career GrowthOur team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future.
US, CA, Santa Clara
Job summaryAWS AI/ML is looking for world class scientists and engineers to join its AI Research and Education group working on building automated ML solutions for planetary-scale sustainability and geospatial applications. Our team's mission is to develop ready-to-use and automated solutions that solve important sustainability and geospatial problems. We live in a time wherein geospatial data, such as climate, agricultural crop yield, weather, landcover, etc., has become ubiquitous. Cloud computing has made it easy to gather and process the data that describes the earth system and are generated by satellites, mobile devices, and IoT devices. Our vision is to bring the best ML/AI algorithms to solve practical environmental and sustainability-related R&D problems at scale. Building these solutions require a solid foundation in machine learning infrastructure and deep learning technologies. The team specializes in developing popular open source software libraries like AutoGluon, GluonCV, GluonNLP, DGL, Apache/MXNet (incubating). Our strategy is to bring the best of ML based automation to the geospatial and sustainability area.We are seeking an experienced Applied Scientist for the team. This is a role that combines science knowledge (around machine learning, computer vision, earth science), technical strength, and product focus. It will be your job to develop ML system and solutions and work closely with the engineering team to ship them to our customers. You will interact closely with our customers and with the academic and research communities. 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. You are also expected to work closely with other applied scientists and demonstrate Amazon Leadership Principles (https://www.amazon.jobs/en/principles). Strong technical skills and experience with machine learning and computer vision are required. Experience working with earth science, mapping, and geospatial data is a plus. Our customers are extremely technical and the solutions we build for them are strongly coupled to technical feasibility.About the teamInclusive Team CultureAt AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon’s culture of inclusion is reinforced within our 14 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust. Work/Life BalanceOur team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.Mentorship & Career GrowthOur team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. Our senior members enjoy one-on-one mentoring. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded scientist and enable them to take on more complex tasks in the future.Interested in this role? Reach out to the recruiting team with questions or apply directly via amazon.jobs.
US, CA, Santa Clara
Job summaryAWS AI/ML is looking for world class scientists and engineers to join its AI Research and Education group working on building automated ML solutions for planetary-scale sustainability and geospatial applications. Our team's mission is to develop ready-to-use and automated solutions that solve important sustainability and geospatial problems. We live in a time wherein geospatial data, such as climate, agricultural crop yield, weather, landcover, etc., has become ubiquitous. Cloud computing has made it easy to gather and process the data that describes the earth system and are generated by satellites, mobile devices, and IoT devices. Our vision is to bring the best ML/AI algorithms to solve practical environmental and sustainability-related R&D problems at scale. Building these solutions require a solid foundation in machine learning infrastructure and deep learning technologies. The team specializes in developing popular open source software libraries like AutoGluon, GluonCV, GluonNLP, DGL, Apache/MXNet (incubating). Our strategy is to bring the best of ML based automation to the geospatial and sustainability area.We are seeking an experienced Applied Scientist for the team. This is a role that combines science knowledge (around machine learning, computer vision, earth science), technical strength, and product focus. It will be your job to develop ML system and solutions and work closely with the engineering team to ship them to our customers. You will interact closely with our customers and with the academic and research communities. 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. You are also expected to work closely with other applied scientists and demonstrate Amazon Leadership Principles (https://www.amazon.jobs/en/principles). Strong technical skills and experience with machine learning and computer vision are required. Experience working with earth science, mapping, and geospatial data is a plus. Our customers are extremely technical and the solutions we build for them are strongly coupled to technical feasibility.About the teamInclusive Team CultureAt AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon’s culture of inclusion is reinforced within our 14 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust. Work/Life BalanceOur team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.Mentorship & Career GrowthOur team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. Our senior members enjoy one-on-one mentoring. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded scientist and enable them to take on more complex tasks in the future.Interested in this role? Reach out to the recruiting team with questions or apply directly via amazon.jobs.
US, NY, New York
Job summaryAmazon Web Services is looking for world class scientists to join the Security Analytics and AI Research team within AWS Security Services. This group is entrusted with researching and developing core data mining and machine learning algorithms for various AWS security services like GuardDuty (https://aws.amazon.com/guardduty/) and Macie (https://aws.amazon.com/macie/). In this group, you will invent and implement innovative solutions for never-before-solved problems. If you have passion for security and experience with large scale machine learning problems, this will be an exciting opportunity.The AWS Security Services team builds technologies that help customers strengthen their security posture and better meet security requirements in the AWS Cloud. The team interacts with security researchers to codify our own learnings and best practices and make them available for customers. We are building massively scalable and globally distributed security systems to power next generation services.Inclusive Team Culture Here at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon’s culture of inclusion is reinforced within our 14 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust. Work/Life Balance Our team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives. Mentorship & Career Growth Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. We care about your career growth and strive to assign projects based on what will help each team member develop and enable them to take on more complex tasks in the future.A day in the lifeAbout the hiring groupJob responsibilities* Rapidly design, prototype and test many possible hypotheses in a high-ambiguity environment, making use of both quantitative and business judgment.* Collaborate with software engineering teams to integrate successful experiments into large scale, highly complex production services.* Report results in a scientifically rigorous way.* Interact with security engineers, product managers and related domain experts to dive deep into the types of challenges that we need innovative solutions for.
US, Virtual
Job summaryDo you have consulting leadership experience deploying digital, data, technology strategy and execution within Fortune 500 enterprise organization? Have you built and led successful consulting practices? Do you have broad technical skills and experience across Machine Learning and Artificial Intelligence? Can you build, lead and influence machine learning engineers and data science consultants in a technical specialty team to deliver these new capabilities on the AWS platform to our enterprise customers? At AWS, we are looking for a Senior Practice Manager with a successful record of leading enterprise customers through a variety of transformative projects involving Machine Learning and Artificial Intelligence; delivering business outcomes that contribute to our customers’ transformation journey. An SPM will focus on a geography and a set of technical specialties, and will manage a team of direct reports. The SPM will develop a long-term plan to develop the right skills across the team, influence the go-to-market strategy within the region and collaborate across the entire AWS organization to bring access to product and service teams, to get the right solution delivered and drive feature innovation based upon customer needs. Key job responsibilities• Engage customers - collaborate with enterprise sales managers to develop strong customer and partner relationships and build a growing business, driving adoption of emerging technologies in key accounts.• Coach and teach - collaborate with field sales, pre-sales, marketing, training and support teams to help partners and customers drive business outcomes through application of AI/ML.• Deliver value - lead high quality delivery of a variety of customized engagements with partners and enterprise customers in the commercial sector.• Lead great people - attract top machine learning engineers and data scientists to build high performing teams of consultants with superior technical depth, and outstanding peer and customer relationship skills• Be a customer advocate - Work with engineering teams to convey partner and enterprise customer feedback as input to technology roadmaps
US, WA, Seattle
Job summaryAWS Insight is looking for a Data Scientist to help develop sophisticated algorithms and models that involve analyzing and learning from over 540 billion customer cost, usage, and utilization events daily. We use this data to generate recommendations and forecasts for customers to help them better understand and optimize their AWS costs and usage and reduce the complexity of managing their cloud costs. Our team's vision is to be the world's authoritative provider of AWS computing insight, where customers can understand, control and optimize usage of AWS products. We sit at the nexus of all AWS services and interact directly with end-customers, and we build relationships with teams across AWS to ensure that we offer a secure and reliable customer experience that builds trust with our customers and provides them with intelligent insights.As a successful data scientist in AWS Insights, you will be responsible for understanding and mining the large amount of data, and developing recommendations that will help improve the accuracy and relevance of our forecasting and recommendations models. You will work closely with talented data scientists, software engineers, and business groups to build enhance existing models and build new models that solve challenging customer problems. You will work with the engineers to drive implementation of the proposed models and establish testing strategies to validate the models before and after they are put into production. On top of that, you are an analytical problem solver who enjoys diving into data, are excited about investigating and developing algorithms, and can influence technical teams and business stakeholders to solve real-world customer problems.Key job responsibilitiesImproving upon existing forecasting statistical or machine learning methodologies by developing new data sources, testing model enhancements, running computational experiments, and fine-tuning model parameters for new forecasting modelsSupporting decision making by providing requirements to develop analytic capabilities, platforms, pipelines and metrics then using them to analyze trends and find root causes of forecast inaccuracyFormalizing assumptions about how demand forecasts are expected to behave, creating definitions of outliers, developing methods to systematically identify these outliers, and explaining why they are reasonable or identifying fixes for themTranslating forecasting business requirements into specific analytical questions that can be answered with available data using statistical and machine learning methods; working with engineers to produce the required data when it is not availableCommunicating verbally and in writing to business customers with various levels of technical knowledge, educating them about our systems, as well as sharing insights and recommendationsUtilizing code (Python, R, Scala, etc.) for analyzing data and building statistical and machine learning models and algorithms
US, Virtual
Job summaryIn the Amazon Selection Monitoring team, we have the goal of establishing the most comprehensive, accurate and fresh universal selection of products. We enrich and increase the quality and coverage of Amazon product selection using cutting edge machine learning and big data technologies. We are looking for highly motivated scientists who can lead the design, development, deployment and maintenance of data-driven models using machine learning (ML) and/or natural language (NL) and computer vision (CV) applications. Your models would be monitoring billions and billions of products. You will build Amazon scale applications running on Amazon Web Service (AWS) that both leverage and create new technologies to process large volumes of data that derive patterns and conclusions from the data. Amazon Science gives you insight into the company’s approach to customer-obsessed scientific innovation. Amazon fundamentally believes that scientific innovation is essential to being the most customer-centric company in the world. It’s the company’s ability to have an impact at scale that allows us to attract some of the brightest minds in artificial intelligence and related fields. Our scientists continue to publish, teach, and engage with the academic community, in addition to utilizing our working backwards method to enrich the way we live and work. Please visit https://www.amazon.science for more information. Responsibilities - Designing and implementing new features and machine learned models, including the application of state-of-art deep learning to solve search matching and ranking problems, including filtering, new content indexing, and apply document understandingConducting and coordinating process development leading to improved and streamlined processes for model development. Strong customer focus is essentialWorking closely with Product Managers to expand depth of our product insights with data, create a variety of experiments, and determine the highest-impact projects to include in planning roadmapsProviding technical and scientific guidance to your team membersCommunicating effectively with senior management as well as with colleagues from science, engineering, and business backgroundsBeing a cultural leader that ensures teams are collecting, understanding, and using data to inform every decision that impacts our customers The successful candidate will have an established background in developing customer-facing experiences, a strong technical ability, a start-up mentality, excellent project management skills, and great communication skills.Key job responsibilitiesDesigning and implementing new features and machine learned models, including the application of state-of-art deep learning to solve search matching and ranking problems, including filtering, new content indexing, and apply document understandingConducting and coordinating process development leading to improved and streamlined processes for model development. Strong customer focus is essentialWorking closely with Product Managers to expand depth of our product insights with data, create a variety of experiments, and determine the highest-impact projects to include in planning roadmapsProviding technical and scientific guidance to your team membersCommunicating effectively with senior management as well as with colleagues from science, engineering, and business backgroundsBeing a cultural leader that ensures teams are collecting, understanding, and using data to inform every decision that impacts our customersA day in the lifeYou will work with Product Managers to translate the business problem into a science problemYou will define methods for data collection and performance evaluationYou will experiment new models and evaluate their performanceYou will perform deep dive to understand potential issues impacting model performance, and form hypotheses for improvementYou will help deploy the model into productionYou will communicate your experimental and production result to Product Managers and business stakeholders
US, Virtual
Job summaryThe AWS Activate Program provides startups the resources they need to grow successfully on AWS. We do this by understanding the uniqueness of each and every startup that applies for Activate, and then personalizing the resources we make available to them. Our resources include (but are not limited to) AWS service credits, Business Support credits, technical education and training, opportunities for business and technical mentorship from Amazonians and startup peers, and personalized growth benefits. The Activate Personalization Team is the brains behind the Activate system. This team is responsible for ingesting startup data from multiple internal and external services, aggregating it into a holistic startup profile, and creating and productionizing ML models. Our team is looking for an experienced Data Scientist (DS) with outstanding leadership skills and the proven ability to build and manage medium-scale modeling projects. The candidate will be an expert across multiple data science domains including data transformation, machine learning, and statistics. Key job responsibilitiesResearch cutting edge algorithms, develop new models, and design and run experiments to improve customer personalizationPartner with scientists, engineers and product leaders to solve business and technology problems using scientific approaches to build new services that surprise and delight our customersCollaborate with BI/Data Engineer teams and drive the collection of new data and the refinement of existing data sources to continually improve data qualityPropose and validate hypothesis to deliver and direct our product road mapConstructively critique peer research and mentor junior scientists and engineers
US, NY, New York
Job summaryWe are open to candidates located in:Seattle, WashingtonPalo Alto, CaliforniaArlington, VirginiaKey job responsibilitiesAs a Senior Research Scientist, you will:Research and develop new methodologies for demand forecasting, alarms, alerts and automation.Apply your advanced data analytics, machine learning skills to solve complex demand planning and allocation problems.Work closely with stakeholders and translate data-driven findings into actionable insights.Improve upon existing methodologies by adding new data sources and implementing model enhancements.Create and track accuracy and performance metrics.Create, enhance, and maintain technical documentation, and present to other scientists, engineers and business leaders.Drive best practices on the team; mentor and guide junior members to achieve their career growth potential.A day in the lifeAbility to utilize exceptional modeling and problem-solving skills to work through different challenges in ambiguous situations.You’ve successfully delivered end-to-end operations research projects, working through conflicting viewpoints and data limitations.You have an enviable level of attention to details.Ability to communicate analytical results to senior leaders, and peers.Innovative scientist with the ability to identify opportunities and develop novel modeling approaches in a fast-paced and ever-changing environment, and gain support with data and storytelling.About the teamVideo advertising is a complex, multi-sided market with many technologies at play within the industry. The industry is rapidly growing and evolving as viewers are shifting from traditional TV viewing to OTT, and from terrestrial radio to streaming. In addition, publishers are increasingly adding video content to their online experiences. Amazon’s video advertising program is a rising competitor in this industry. Amazon’s service has differentiated assets in our customer & audience insights, exclusive video content and associated inventory on our streaming services (IMDbTV, Twitch, Prime Video, Amazon Music, etc.) and devices (FireTV, Echo, Fire Tablet) which all position us well as an end to end service for advertisers and agencies. As our business grows, we are continually experimenting with a portfolio of emerging ideas and technology as well as global expansion. We are looking for passionate, hard-working, and talented individuals to help foster these nascent ideas into scalable products and launch them into the market.