Social
cmu-magnus.jpg
Location: Provo, UT, USA
Faculty advisor: Alan Black

Magnus

This team, consisting of PhD and Masters students from Carnegie Mellon University, brings together experience in chatbot interaction strategies, question answering, neural modeling and machine learning.

By Carnegie Mellon University
4 min read
Share

The team's vision is to build a social bot that can engage users in conversations apart from answering factual queries or performing everyday tasks. In order to facilitate high quality interaction with users, the conversation with the agent should evolve by leveraging mechanisms that establish coherence with user feedback and reactions. In order to engage users in a coherent manner, it would be useful if the agent plans the conversation ahead in time.

Shrimai P. - Team leader

I am a second year Master of Language Technologies student at the School of Computer Science. I am advised by Prof. Alan W. Black and Prof. Carolyn Rose. I am broadly interested in natural language processing and machine learning. Specifically, my research focuses of the various aspects of spoken dialog systems. Currently I am working on language generation for influential style of writing. Before joining CMU, I worked as an Analyst at Goldman Sachs, India on virtualization and operating systems. In my undergraduate program, I worked on building a question answering system for the semantic web.

Abhilasha R.

I am a first year student in the Master's in Language Technologies program. I am currently pursuing research in ubiquitous personal assistants and grounded semantics under Prof. Eric Nyberg. My previous research has been in problems related to parameterized complexity in Ki,j-free graphs and in analyzing social behavior through vision. I also spent a brief time in the industry. I interned at Amazon for six months, and later worked at a Computer Vision startup. My main interests lie in problems related to machine learning, NLP and algorithms.

Akash B.

I'm a graduate student who works at the intersection of Natural Language Processing and Machine Learning. My work in these domains has appeared in top tier conferences such as ICML, EMNLP, AAAI and ITS.

Chaitanya M.

My current research focus is on incorporating external knowledge into neural machine translation. I graduated from Nanyang Technological University, Singapore last year and worked on a range of applied machine learning and NLP projects. A few of these include detecting fraud and stock price changes by building a knowledge graph from entity recognition in financial reports; a context-based recommender system for events; and behavioral modeling for traffic simulation. I am excited about conversational dialog systems and very interested in several aspects such as building context-aware systems, and semantic parsing.

Esha Ashesh K.

I am a graduate student in the Language Technologies Institute in the School of Computer Science, majoring in Computational Data Science (MCDS), Analytics track. My research interests are focused towards natural language processing, dialog systems, and speech processing. I am presently assisting Prof. Alan Black in teaching the graduate level Natural Language Processing course. I also interned at Microsoft, Redmond as a Data Science Intern in Summer 2016. Before starting at CMU, I graduated from the National Institute of Technology, Goa, India with a major in computer science and engineering.

Fadi B.

N/A

Rama Kumar P.

I am currently pursuing a Master's in Language Technology in School of Computer Science, solving exciting problems in ML/NLP applied on large scale datasets! My research interests are in Big Data Analytics, Scalable Machine learning, Convex and Submodular Optimization applied in areas such as Graph mining, text analytics and Social Network Analysis. I pursued my Bachelor's and Master's at the Indian institute of Technology, Madras from the department of Electrical Engineering. I previously worked as a Research Engineer at Big Data Labs, American Express and in the Business Analytics and Math Sciences department, IBM India Research Lab, Bangalore, India.

Shivani P.

I am a Master's student in the LTI department. I work on modelling user trajectories from social media. I have also worked extensively on probabilistic models borrowing from user psychology research.

Tom M.

I am a first year Master's of Language Technologies Student. I graduated from Rensselaer Polytechnic Institute in the Spring of 2016 with a BS in computer science. While there I participated on multiple research projects with both Prof. James Hendler, and Prof. Mei Si in projects related to machine learning, question answering, and knowledge representation. Additionally I have had internships with Pinterest, LinkedIn, Bloomberg LP, and Hover Inc. Currently I am working with Prof. Eric Nyberg at CMU on automated question answering in smart home settings.

Xinrui H.

I'm a first-year graduate student in the M.S. program in Intelligent Information Systems (MIIS) at Language Technologies Institute (LTI). My research interests fall in Information Retrieval, Dialogue System and Machine Learning. I graduated with a Bachelor of Science degree, SUMMA CUM LAUDE from Peking University in 2016.

Zhou Y.

I am a PhD student at the Language Technology Institute under School of Computer Science, working with Prof. Alan W Black and Prof. Alexander I. Rudnicky in LTI. In Summer 2015 and 2016 I interned with Prof. David Suendermann-Oeft in ETS San Francisco Office working on cloud based mulitmodal dialog systems. In Fall 2014, I interned with Dan Bohus and Eric Horvitz in Microsoft Research working on situated multimodal dialogue systems.

Alan Black - Faculty advisor

Professor of Computer Science in the Language Technologies Institute in the School of Computer Science. I am a world leader in speech synthesis, spoken dialog and speech-to-speech translations. I have over 200 referred papers, and am one of the highest cited authors in the speech community (Interspeech).

About the Author
Carnegie Mellon University

Latest news

The latest updates, stories, and more about Alexa Prize.
Load more

Work with us

See more jobs See more jobs
Applied Scientist III, Amazon - Ads Nova
US, NY, New York
Are you passionate about solving big problems from ground-up? Do you enjoy building new state-of-the-art products at internet scale? Come lead the innovation in this startup team, vertical ad products. This is a green field problem without a known answer or a pattern to follow. We have ambitious vision to simplify full funnel advertising solutions, at scale, with specialized agentic AI-powered models and diversify the demand to strategic verticals including finserv, autos, locals.. etc. We are seeking an experienced Applied Scientist to drive innovation in our Ads Foundational Model. In this individual contributor role, you will apply advanced machine learning techniques to improve advertiser performance and customer experience. Key job responsibilities As an Applied Scientist on this team, you will: 1. Develop and drive the science strategy for Ads Foundational Model (Ads-FM), aligning it with the program's objectives and overall business goals. 2. Identify high-impact opportunities within Ads-FM program and lead the ideation, planning, and execution of science initiatives to address them. 3. Build and deploy machine learning models using computer vision, natural language processing, and deep learning to evaluate and enhance ad effectiveness. 4. Develop algorithms that extract meaningful signals from image, video, and audio content to predict and improve customer engagement 5. Leverage Amazon's extensive data repository to create predictive models that generate actionable recommendations for more compelling ad creative 6. Collaborate with business leaders and cross-functional teams to implement ML-powered solutions 7. Contribute to the ML roadmap for the Ads-FM program through innovation and research.
Principal Economist, Stores Economics and Science
US, WA, Seattle
This role will contribute to developing the Economics and Science products and services in the Fee domain, with specialization in supply chain systems and fees. Through the lens of economics, you will develop causal links for how Amazon, Sellers and Customers interact. You will be a key and senior scientist, advising Amazon leaders how to price our services. You will work on developing frameworks and scaleable, repeatable models supporting optimal pricing and policy in the two-sided marketplace that is central to Amazon's business. The pricing for Amazon services is complex. You will partner with science and technology teams across Amazon including Advertising, Supply Chain, Operations, Prime, Consumer Pricing, and Finance. We are looking for an experienced Principal Economist to improve our understanding of seller Economics, enhance our ability to estimate the causal impact of fees, and work with partner teams to design pricing policy changes. In this role, you will provide guidance to scientists to develop econometric models to influence our fee pricing worldwide. You will lead the development of causal models to help isolate the impact of fee and policy changes from other business actions, using experiments when possible, or observational data when not. Key job responsibilities The ideal candidate will have extensive Economics knowledge, demonstrated strength in practical and policy relevant structural econometrics, strong collaboration skills, proven ability to lead highly ambiguous and large projects, and a drive to deliver results. They will work closely with Economists, Data / Applied Scientists, Strategy Analysts, Data Engineers, and Product leads to integrate economic insights into policy and systems production. Familiarity with systems and services that constitute seller supply chains is a plus but not required. About the team The Stores Economics and Sciences team is a central science team that supports Amazon's Retail and Supply Chain leadership. We tackle some of Amazon's most challenging economics and machine learning problems, where our mandate is to impact the business on massive scale.
Quantum Research Engineer, Quantum Computing
US, CA, Pasadena
The Amazon Center for Quantum Computing (CQC) team is looking for a passionate, talented, and inventive Research Engineer specializing in hardware design for cryogenic environments. The ideal candidate should have expertise in 3D CAD (SolidWorks), thermal and structural FEA (Ansys/COMSOL), hardware design for cryogenic applications, design for manufacturing, and mechanical engineering principles. The candidate must have demonstrated experience driving designs through full product development cycles (requirements, conceptual design, detailed design, manufacturing, integration, and testing). Candidates must also have a strong background in both cryogenic mechanical engineering theory and implementation. Working effectively within a cross-functional team environment is critical. Key job responsibilities The CQC collaborates across teams and projects to offer state-of-the-art, cost-effective solutions for scaling the signal delivery to quantum processor systems at cryogenic temperatures. Equally important is the ability to scale the thermal performance and improve EMI mitigation of the cryogenic environment. You will work on the following: - High density novel packaging solutions for quantum processor units - Cryogenic mechanical design for novel cryogenic signal conditioning sub-assemblies - Cryogenic mechanical design for signal delivery systems - Simulation-driven designs (shielding, filtering, etc.) to reduce sources of EMI within the qubit environment. - Own end-to-end product development through requirements, design reports, design reviews, assembly/testing documentation, and final delivery A day in the life As you design and implement cryogenic hardware solutions, from requirements definition to deployment, you will also: - Participate in requirements, design, and test reviews and communicate with internal stakeholders - Work cross-functionally to help drive decisions using your unique technical background and skill set - Refine and define standards and processes for operational excellence - Work in a high-paced, startup-like environment where you are provided the resources to innovate quickly About the team The Amazon Center for Quantum Computing (CQC) is a multi-disciplinary team of scientists, engineers, and technicians, on a mission to develop a fault-tolerant quantum computer. Inclusive Team Culture Here at Amazon, 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 conferences, inspire us to never stop embracing our uniqueness. Diverse Experiences Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. 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. Export Control Requirement Due to applicable export control laws and regulations, candidates must be either a U.S. citizen or national, U.S. permanent resident (i.e., current Green Card holder), or lawfully admitted into the U.S. as a refugee or granted asylum, or be able to obtain a US export license. If you are unsure if you meet these requirements, please apply and Amazon will review your application for eligibility.
Microwave Design Engineer, Amazon Center for Quantum Computing
US, CA, Pasadena
The Amazon Center for Quantum Computing in Pasadena, CA, is looking to hire an Applied Scientist specializing in the design of microwave components for use in cryogenic environments. Working alongside other scientists and engineers, you will design and validate hardware performing microwave signal conditioning at cryogenic temperatures for Amazon quantum processors. Working effectively within a cross-functional team environment is critical. The ideal candidate will have a proven track record of hardware development from requirements development to validation. Diverse Experiences Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. 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. 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 and 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. Key job responsibilities Our scientists and engineers collaborate across diverse teams and projects to offer state of the art, cost effective solutions for the signal conditioning of Amazon quantum processor systems at cryogenic temperatures. You’ll bring a passion for innovation, collaboration, and mentoring to: Solve layered technical problems across our cryogenic signal chain. Develop requirements with key system stakeholders, including quantum device, test and measurement, hardware, and theory teams. Design, implement, test, deploy, and maintain innovative solutions that meet both performance and cost metrics. Research enabling technologies necessary for Amazon reach commercial viability in quantum computing . A day in the life As you research, design, and implement cryogenic microwave signal conditioning solutions, you will also: Participate in requirements, design, and test reviews. Work cross-functionally to help drive decisions using your unique technical background and skill set. Define and maintain standards for operational excellence. Work in a high-paced, startup-like environment where you are provided the resources to innovate quickly.
Applied Scientist, Alexa AI
IT, Turin
As an Applied Scientist in the Alexa AI team, you will spearhead the advancement and deployment of state-of-the-art ML/RAG systems that revolutionize how millions of customers interact with Alexa. You'll leverage your expertise in machine learning, natural language processing, and large language models to create reliable, scalable, high-performance products that set new standards in operational excellence. Working at the intersection of research and production, you'll translate latest AI innovations into customer-facing features that delight users daily. Your work will span the full ML lifecycle—from analyzing customer behavior patterns and building novel metrics for personal digital assistants, to deploying automated training pipelines and conducting rigorous A/B testing across diverse devices and endpoints. Collaborating closely with business, engineering, and science teams across Amazon, you'll lead high-visibility programs that automate workflows and deliver measurable customer impact. This role offers the unique opportunity to publish at top-tier conferences while seeing your innovations scale to one of the world's most popular voice assistants, serving millions of customers globally. Key job responsibilities As an Applied Scientist in the Alexa AI team: - You'll analyze and model customer behavior at scale, building novel metrics for personal digital assistants across diverse devices and endpoints. Your work will involve creating deep learning, policy-based learning, and machine learning algorithms that directly impact customer experiences, translating complex data patterns into actionable insights that drive product innovation. - Your technical leadership will extend to building and deploying automated model training and evaluation pipelines, implementing complex machine learning and deep learning algorithms, and conducting rigorous model and data analysis through online A/B testing. You'll research and implement novel approaches that push the boundaries of what's possible in conversational AI. - Beyond model development, you'll ensure operational excellence by taking ownership of production systems, including on-call responsibilities during peak and non-peak hours. Working alongside Software Development Engineers, you'll deploy fixes and handle high-severity issues, ensuring our ML systems maintain the reliability and performance that millions of Alexa customers depend on daily. A day in the life As an Applied Scientist in the Alexa AI team, your day will involve collaborating with talented engineers and scientists to build scalable solutions for our conversational assistant. You'll dive into data analysis, experiment with novel algorithms, and iterate on models based on real-time user feedback. Working in a fast-paced, ambiguous environment, you'll tackle complex technical challenges—from debugging production issues to presenting research findings to stakeholders. Your self-motivated approach will drive you to swiftly deliver impactful solutions while maintaining the high standards that define our mission to revolutionize user experiences for millions of customers. About the team The Alexa AI team develops the intelligence behind one of the world's most popular voice assistants, serving millions of customers globally. We're a diverse group of scientists, engineers, and researchers united by our mission to make Alexa more natural, helpful, and delightful. Our culture thrives on innovation, collaboration, and customer obsession. We tackle some of the most challenging problems in conversational AI—from natural language understanding to personalization at scale. Here, you'll work alongside world-class talent, publish at top-tier conferences, and see your innovations impact customers daily. We move fast, think big, and celebrate both successes and learnings.
Applied Scientist, Alexa AI
IT, Turin
As an Applied Scientist in the Alexa AI team, you will spearhead the advancement and deployment of state-of-the-art ML/RAG systems that revolutionize how millions of customers interact with Alexa. You'll leverage your expertise in machine learning, natural language processing, and large language models to create reliable, scalable, high-performance products that set new standards in operational excellence. Working at the intersection of research and production, you'll translate latest AI innovations into customer-facing features that delight users daily. Your work will span the full ML lifecycle—from analyzing customer behavior patterns and building novel metrics for personal digital assistants, to deploying automated training pipelines and conducting rigorous A/B testing across diverse devices and endpoints. Collaborating closely with business, engineering, and science teams across Amazon, you'll lead high-visibility programs that automate workflows and deliver measurable customer impact. This role offers the unique opportunity to publish at top-tier conferences while seeing your innovations scale to one of the world's most popular voice assistants, serving millions of customers globally. Key job responsibilities As an Applied Scientist in the Alexa AI team: - You'll analyze and model customer behavior at scale, building novel metrics for personal digital assistants across diverse devices and endpoints. Your work will involve creating deep learning, policy-based learning, and machine learning algorithms that directly impact customer experiences, translating complex data patterns into actionable insights that drive product innovation. - Your technical leadership will extend to building and deploying automated model training and evaluation pipelines, implementing complex machine learning and deep learning algorithms, and conducting rigorous model and data analysis through online A/B testing. You'll research and implement novel approaches that push the boundaries of what's possible in conversational AI. - Beyond model development, you'll ensure operational excellence by taking ownership of production systems, including on-call responsibilities during peak and non-peak hours. Working alongside Software Development Engineers, you'll deploy fixes and handle high-severity issues, ensuring our ML systems maintain the reliability and performance that millions of Alexa customers depend on daily. A day in the life As an Applied Scientist in the Alexa AI team, your day will involve collaborating with talented engineers and scientists to build scalable solutions for our conversational assistant. You'll dive into data analysis, experiment with novel algorithms, and iterate on models based on real-time user feedback. Working in a fast-paced, ambiguous environment, you'll tackle complex technical challenges—from debugging production issues to presenting research findings to stakeholders. Your self-motivated approach will drive you to swiftly deliver impactful solutions while maintaining the high standards that define our mission to revolutionize user experiences for millions of customers. About the team The Alexa AI team develops the intelligence behind one of the world's most popular voice assistants, serving millions of customers globally. We're a diverse group of scientists, engineers, and researchers united by our mission to make Alexa more natural, helpful, and delightful. Our culture thrives on innovation, collaboration, and customer obsession. We tackle some of the most challenging problems in conversational AI—from natural language understanding to personalization at scale. Here, you'll work alongside world-class talent, publish at top-tier conferences, and see your innovations impact customers daily. We move fast, think big, and celebrate both successes and learnings.
Applied Scientist, Alexa AI
IT, Turin
As an Applied Scientist in the Alexa AI team, you will spearhead the advancement and deployment of state-of-the-art ML/RAG systems that revolutionize how millions of customers interact with Alexa. You'll leverage your expertise in machine learning, natural language processing, and large language models to create reliable, scalable, high-performance products that set new standards in operational excellence. Working at the intersection of research and production, you'll translate latest AI innovations into customer-facing features that delight users daily. Your work will span the full ML lifecycle—from analyzing customer behavior patterns and building novel metrics for personal digital assistants, to deploying automated training pipelines and conducting rigorous A/B testing across diverse devices and endpoints. Collaborating closely with business, engineering, and science teams across Amazon, you'll lead high-visibility programs that automate workflows and deliver measurable customer impact. This role offers the unique opportunity to publish at top-tier conferences while seeing your innovations scale to one of the world's most popular voice assistants, serving millions of customers globally. Key job responsibilities As an Applied Scientist in the Alexa AI team: - You'll analyze and model customer behavior at scale, building novel metrics for personal digital assistants across diverse devices and endpoints. Your work will involve creating deep learning, policy-based learning, and machine learning algorithms that directly impact customer experiences, translating complex data patterns into actionable insights that drive product innovation. - Your technical leadership will extend to building and deploying automated model training and evaluation pipelines, implementing complex machine learning and deep learning algorithms, and conducting rigorous model and data analysis through online A/B testing. You'll research and implement novel approaches that push the boundaries of what's possible in conversational AI. - Beyond model development, you'll ensure operational excellence by taking ownership of production systems, including on-call responsibilities during peak and non-peak hours. Working alongside Software Development Engineers, you'll deploy fixes and handle high-severity issues, ensuring our ML systems maintain the reliability and performance that millions of Alexa customers depend on daily. A day in the life As an Applied Scientist in the Alexa AI team, your day will involve collaborating with talented engineers and scientists to build scalable solutions for our conversational assistant. You'll dive into data analysis, experiment with novel algorithms, and iterate on models based on real-time user feedback. Working in a fast-paced, ambiguous environment, you'll tackle complex technical challenges—from debugging production issues to presenting research findings to stakeholders. Your self-motivated approach will drive you to swiftly deliver impactful solutions while maintaining the high standards that define our mission to revolutionize user experiences for millions of customers. About the team The Alexa AI team develops the intelligence behind one of the world's most popular voice assistants, serving millions of customers globally. We're a diverse group of scientists, engineers, and researchers united by our mission to make Alexa more natural, helpful, and delightful. Our culture thrives on innovation, collaboration, and customer obsession. We tackle some of the most challenging problems in conversational AI—from natural language understanding to personalization at scale. Here, you'll work alongside world-class talent, publish at top-tier conferences, and see your innovations impact customers daily. We move fast, think big, and celebrate both successes and learnings.
Applied Scientist, Alexa AI
IT, Turin
As an Applied Scientist in the Alexa AI team, you will spearhead the advancement and deployment of state-of-the-art ML/RAG systems that revolutionize how millions of customers interact with Alexa. You'll leverage your expertise in machine learning, natural language processing, and large language models to create reliable, scalable, high-performance products that set new standards in operational excellence. Working at the intersection of research and production, you'll translate latest AI innovations into customer-facing features that delight users daily. Your work will span the full ML lifecycle—from analyzing customer behavior patterns and building novel metrics for personal digital assistants, to deploying automated training pipelines and conducting rigorous A/B testing across diverse devices and endpoints. Collaborating closely with business, engineering, and science teams across Amazon, you'll lead high-visibility programs that automate workflows and deliver measurable customer impact. This role offers the unique opportunity to publish at top-tier conferences while seeing your innovations scale to one of the world's most popular voice assistants, serving millions of customers globally. Key job responsibilities As an Applied Scientist in the Alexa AI team: - You'll analyze and model customer behavior at scale, building novel metrics for personal digital assistants across diverse devices and endpoints. Your work will involve creating deep learning, policy-based learning, and machine learning algorithms that directly impact customer experiences, translating complex data patterns into actionable insights that drive product innovation. - Your technical leadership will extend to building and deploying automated model training and evaluation pipelines, implementing complex machine learning and deep learning algorithms, and conducting rigorous model and data analysis through online A/B testing. You'll research and implement novel approaches that push the boundaries of what's possible in conversational AI. - Beyond model development, you'll ensure operational excellence by taking ownership of production systems, including on-call responsibilities during peak and non-peak hours. Working alongside Software Development Engineers, you'll deploy fixes and handle high-severity issues, ensuring our ML systems maintain the reliability and performance that millions of Alexa customers depend on daily. A day in the life As an Applied Scientist in the Alexa AI team, your day will involve collaborating with talented engineers and scientists to build scalable solutions for our conversational assistant. You'll dive into data analysis, experiment with novel algorithms, and iterate on models based on real-time user feedback. Working in a fast-paced, ambiguous environment, you'll tackle complex technical challenges—from debugging production issues to presenting research findings to stakeholders. Your self-motivated approach will drive you to swiftly deliver impactful solutions while maintaining the high standards that define our mission to revolutionize user experiences for millions of customers. About the team The Alexa AI team develops the intelligence behind one of the world's most popular voice assistants, serving millions of customers globally. We're a diverse group of scientists, engineers, and researchers united by our mission to make Alexa more natural, helpful, and delightful. Our culture thrives on innovation, collaboration, and customer obsession. We tackle some of the most challenging problems in conversational AI—from natural language understanding to personalization at scale. Here, you'll work alongside world-class talent, publish at top-tier conferences, and see your innovations impact customers daily. We move fast, think big, and celebrate both successes and learnings.
Human-Robot Interaction Applied Scientist , Fauna
US, NY, New York
We are seeking a Human-Robot Interaction (HRI) Applied Scientist to develop cutting-edge interactions that make robots feel alive, personal, and fun. In this role, you will focus on verbal and non-verbal conversational systems, social dynamics, memory, and long-term relationship formation between robots, their environments, and the people they interact with. Your contributions will be essential in advancing robotics by enabling expressive, socially intelligent, and trustworthy interactions between robots and humans. Key job responsibilities - Develop interactive systems that leverage large language models, multimodal inputs and outputs, reinforcement learning from human feedback, or other advanced techniques to achieve fluid, engaging, and socially appropriate robot behavior - Design and implement intelligent conversational systems that handle turn-taking, grounding, interruption, and incorporates context drawn from a robot's physical environment and shared history with a user - Integrate perceptual sensor streams including gaze, facial expression, gesture, posture, and more to understand social context and produce coherent, lifelike interactions. - Develop memory and personalization systems that allow robots to form lasting relationships with individual users, learn their environments, and adapt their behavior over weeks and months - Stay updated on advancements in HRI, NLP, multimodal AI, and cognitive and social science to apply cutting-edge techniques to robot interaction challenges - Lead technical projects from conception through production deployment - Mentor junior scientists and engineers - Bridge research initiatives with practical engineering implementation
Applied Scientist, Agentic Automated Reasoning
GB, London
The Agentic Automated Reasoning Group is building the next generation of software verification tools combining advances in artificial intelligence, the computational capacity of the cloud, and our deep expertise in the domain. Join us if you want to be a part of this transformational endeavor. The Strata team (https://github.com/strata-org) is seeking an applied scientist with broad interest and expertise in model checking, interactive theorem proving, programming language semantics, and generative AI. You will combine your expertise with that of your coworkers to build new tools that solve code analysis problems previously considered beyond reach. Our application areas span all the way from Infrastructure as Code to high-performance cryptography written in assembly code, while our methods span from interactive theorem proving to automated test generation. Each day, hundreds of thousands of developers make billions of transactions worldwide on AWS. They harness the power of the cloud to enable innovative applications, websites, and businesses. Using automated reasoning technology and mathematical proofs, AWS allows customers to answer questions about security, availability, durability, and functional correctness. We call this provable security, absolute assurance in security of the cloud and in the cloud. https://aws.amazon.com/security/provable-security/ Key job responsibilities - Work with customer teams to understand the nature of their software and the properties they need to establish of it. - Identify tools and methods capable of addressing the verification needs of customers, including any novel analysis capabilities required. - Use techniques spanning property-based testing to model checkers, and interactive theorem provers to establish program properties. - Explore generative AI techniques to help customers formalize their requirements, find revealing tests, generate required boiler plate for testing and model checking, and find and repair program proofs. About the team The Agentic Automated Reasoning Group at AWS develops and applies state of the art formal methods and automated reasoning techniques to ensure the security, reliability, and correctness of AWS services and customer applications, with a strong focus on AI based agents. Our work innovates tools and services to perform verification at scale and apply them to build safe and secure systems at AWS. We are also pioneering the use of formal verification and automated reasoning to develop agentic systems, ensuring AI agents operate within defined safety boundaries.
See more jobs
View from space of a connected network around planet Earth representing the Internet of Things.
Get more from Amazon Science
Subscribe to our newsletter

Amazon.com | Conditions of Use | Privacy | © 1996-2026 Amazon.com, Inc. or its affiliates

Social