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knowledge management machine learning operations research and optimization quantum technologies robotics search and information retrieval security privacy and abuse prevention sustainability our scientific contributions publications research from our scientists and collaborators conferences our experts present and discuss cutting edge research at scientific meetings globally news blog the latest from amazon researchers amazon science blog technical deep dives and perspectives from our scientists news research milestones and recent achievements the latest from amazon researchers amazon science blog technical deep dives and perspectives from our scientists news research milestones and recent achievements collaborations amazon research awards overview call for proposals latest news research stories recipients amazon nova ai challenge overview rules faqs teams research collaborations overview carnegie mellon university columbia university hampton university howard university iit bombay johns hopkins university max planck society mit tennessee state university university of california los angeles university of illinois urbana champaign university of southern california university of texas at austin virginia tech university of washington amazon research awards overview call for proposals latest news research stories recipients amazon nova ai challenge overview rules faqs teams research collaborations overview carnegie mellon university columbia university hampton university howard university iit bombay johns hopkins university max planck society mit tennessee state university university of california los angeles university of illinois urbana champaign university of southern california university of texas at austin virginia tech university of washington resources code and datasets amazon nova try amazon s frontier foundation models code and datasets amazon nova try amazon s frontier foundation models careers careers explore our open roles amazon scholars faculty research opportunities on industry scale technical challenges postdoctoral science program early career research opportunities alongside experienced industry scientists careers explore our open roles amazon scholars faculty research opportunities on industry scale technical challenges postdoctoral science program early career research opportunities alongside experienced industry scientists search submit search why don t machine learning research agents overfit new research indicates that ai agents learn compressible models of data which don t have enough space to enable memorization read more developing provably correct rust code with verus how the verus program verifier which automatically checks code against a mathematical specification of its functionality helps increase security assurance in software projects read more a decade of mathematical certainty ten years after we founded the automated reasoning group mathematical logic has moved from academic research into production services that secure millions of customer workloads demonstrating that systems can be provably correct not just probably correct read more a new benchmark for evaluating patient facing health ai agents patientagentbench generates a synthetic patient health record a realistic clinical vignette and a patient agent that converses with the ai system under evaluation to capture what a patient facing agent actually has to do read more graviton5 s improved design increases speed and energy efficiency beyond moore s law a new chiplet architecture custom die to die connectivity and support for ddr5 8800 memory and the latest pcie gen6 interconnects improve performance by 25 for general purpose and agentic ai workloads read more amazon news why don t machine learning research agents overfit developing provably correct rust code with verus a decade of mathematical certainty a new benchmark for evaluating patient facing health ai agents graviton5 s improved design increases speed and energy efficiency beyond moore s law customer obsessed science our approach research areas automated reasoning cloud and systems computer vision conversational ai economics information and knowledge management machine learning operations research and optimization quantum technologies robotics search and information retrieval security privacy and abuse prevention sustainability from the blog view all technical deep dives and perspectives from our scientists view all advancing ai for biology teaching models to design and characterize antibodies september 21 2026 11 min read three new papers from amazon bio discovery address bottlenecks in ai driven antibody engineering from benchmarking binding predictors to experimentally validating de novo design machine learning when llm judges agree should we believe them august 26 2026 5 min read conversational ai sop bench a new benchmark for evaluating ai agents on real business procedures august 21 2026 9 min read conversational ai how controllers from industrial machinery can coordinate multitask machine learning july 30 2026 8 min read machine learning amazon and university of michigan give robots a sense of touch july 10 2026 5 min read robotics view all featured news 34 amazon research awards build on trainium recipients announced the build on trainium program is a 110 million credit initiative supporting ai research at 30 universities including stanford uc berkeley uiuc ucla cmu and mit with a focus on responsible ai aws and hopkins engineering announce database for ai ml antibody design the antibody developability benchmark is powered by one of the most diverse antibody datasets in public literature enabling transparent performance evaluation for ai guided antibody design 2026 amazon nova ai challenge trusted software agents track challenge pushes teams to demonstrate measurable gains in secure coding performance while building ai agents that advance real world utility and reliability at scale amazon launches 68 million ai phd fellowship program initiative will fund over 100 doctoral students researching machine learning computer vision and natural language processing at nine universities publications view all view all bee private compute privacy preserving intelligence for bee steve korshakov karan lyons ethan sutin jonathan pugh aleksei zinchenko alessandro eppacher billy jang brian taylor nicholas anderson cole collins diksha aurobindo ali mirza 2026 bee provides a personal ai assistant that uses frontier ai models over user controlled real world context privacy is a core system requirement the architecture is designed to prevent bee and other amazon operators non attested internal services and supporting infrastructure from accessing plaintext user data outside the user s cryptographically authorized processing path the bee private compute architecture security privacy and abuse prevention deploying programmatic tool calling with pre execution validation for production agentic systems nhan nguyen hadi habibzadeh ahmad magdy eid emnlp 2026 2026 production tool calling for agentic systems must satisfy four operational requirements lower per invocation cost low latency adaptability to evolving tool catalogs and the ability to catch errors before execution the react paradigm keeps the large language model llm in the loop but at production scale reprocessing intermediate results inflates cost and latency and degrades answer quality programmatic cloud and systems trace traceable root cause analysis with calibrated evidence grounded agents aniket joshi cyrus dsouza sejal jain manjunath channappagoudar emnlp 2026 2026 root cause analysis rca for defects in large e commerce enterprises is manual and slow a single defect spanning thousands of microservices and sops takes experts one to two weeks to diagnose generic agentic rca frameworks fail on this workload because they stop at proximate causes cannot verify numeric claims ignore past reviewer decisions and return enumerated hypotheses rather than the quantified automated reasoning on optical add drop multiplexing architecture for hyperscale backbone networks ahmad abdo psc 2026 international conference on photonics in switching and computing 2026 we analyze optical add drop multiplexing architecture trade offs for cloud content providers focusing on g snr operations reliability and cost power we show that as coherent baud rates increase directly attaching transponders to the wss satisfies all key metrics cloud and systems beyond the harness end to end optimization of context artifacts for enterprise text to sql kate gwimm carson eisenach colm 2026 workshop on context beyond the window 2026 deploying llms for enterprise text to sql is bottlenecked less by the model than by what context reaches it business logic spans thousands of tables and no model can ingest a full catalog at once we argue that the most effective place to intervene is therefore the knowledge base context the model consumes and that this context should be constructed from historical usage rather than tuned for as a fixed machine learning load more collaborations view all whether you re a faculty member or student there are number of ways you can engage with amazon view all gretchen ertl amazon research awards the program offers unrestricted funds and other resources to support research at academic institutions and non profit organizations in areas that align with our mission amazon nova ai challenge a global university competition to drive secure innovation in generative ai technology which focuses on responsible ai and large language model coding security credit wolfram scheible research collaborations we partner with particular academic organizations across the world for deep and sustained collaborations in multiple research areas of mutual interest courtesy of pai ling yin amazon scholars we hire world class academics to work on large scale technical challenges while they continue to teach and conduct research at their universities view all work with us see more jobs see more jobs applied scientist neuron arg annapurna ml us wa seattle are you a phd interested in machine learning natural language processing computer vision automated reasoning robotics or quantum technologies we are looking for skilled scientists capable of putting theory into practice through experimentation and invention leveraging science techniques and implementing systems to work on massive datasets in an effort to tackle never before solved problems a successful candidate will be a self starter comfortable with ambiguity strong attention to detail and the ability to work in a fast paced ever changing environment as an applied scientist you will own the design and development of end to end systems you ll have the opportunity to create technical roadmaps and drive production level projects that will support amazon science you will work closely with amazon scientists and other science interns to develop solutions and deploy them into production the ideal scientist must have the ability to work with diverse groups of people and cross functional teams to solve complex business problems key job responsibilities amazon science gives 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 use our working backwards method to enrich the way we live and work for more information on the amazon science community please visit https www amazon science applied scientist catalog system services science us wa seattle at amazon selection and catalog systems ascs our mission is to power the online buying experience for customers worldwide so they can find discover and buy any product they want we innovate on behalf of our customers to ensure uniqueness and consistency of product identity and to infer relationships between products in amazon catalog to drive the selection gateway for the search and browse experiences on the website we re solving a fundamental ai challenge establishing product relevant information at unprecedented scale with frontier models and agents the scale is staggering billions of products petabytes of multimodal data millions of sellers dozens of languages and infinite product diversity ranging from electronics to groceries to digital content the research challenges are immense genai and vlms hold transformative promise for catalog understanding but we operate where traditional methods fail ambiguous problem spaces incomplete and noisy data inherent uncertainty reasoning across both images and textual data and explaining decisions at scale enriching product information requires sophisticated models that reason across text images and structured data all while maintaining accuracy and trust for high stakes business decisions affecting millions of customers daily amazon s catalog system services science team is looking for an innovative and customer focused applied scientist to help us make the world s best product catalog even better in this role you will partner with technology and business leaders to build new state of the art algorithms models and services you will pioneer advanced genai solutions that power next generation agentic shopping experiences working in a collaborative environment where you can experiment with massive data from the world s largest product catalog tackle problems at the frontier of ai research rapidly implement and deploy your algorithmic ideas at scale across millions of customers key job responsibilities formulate novel research problems at the intersection of genai multimodal learning and large scale information retrieval in essence translating ambiguous business challenges into tractable scientific frameworks design and implement leading models leveraging frontier models and agentic architectures to enrich catalog information at billion product scale pioneer explainable ai methodologies that balance model performance with scalability requirements for production systems impacting millions of daily customer decisions own end to end ml pipelines from research ideation to production deployment processing petabytes of multimodal data with rigorous evaluation frameworks represent the team in the broader science community publishing findings delivering tech talks and staying at the forefront of genai vlm and agentic system research senior applied scientist amazon connect us ny new york are you excited about applying machine learning and statistical modeling to real world systems that serve millions of customers amazon connect is a cloud based contact center service that helps businesses deliver personal efficient customer experiences our team of scientists and engineers builds the ai and ml capabilities that power contact center operations and o...
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