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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 research scientist mobile manipulation robotics i o us ma north reading amazon robotics is transforming warehouse automation through edge ai and machine learning applied to real world robotics challenges we re seeking a research scientist to advance our mobile manipulation capabilities by developing novel learning based approaches that enable robots to navigate and manipulate objects in dynamic fulfillment environments this role offers the opportunity to conduct original research and translate state of the art findings into production systems operating at amazon s unprecedented scale key job responsibilities research and algorithm development formulate novel research problems in robot learning and manipulation design new model architectures validate hypotheses through rigorous experimentation and advance the state of the art in learning based robotics data strategy and pipeline design define data requirements for research initiatives design scalable collection and curation strategies establish governance and provenance standards and build reusable pipelines ensuring data quality and reproducibility experimentation and scientific validation design and execute experiments in simulation and real world embodiments develop evaluation methodologies and benchmarks perform ablation studies and statistical analyses and iterate systematically to advance model performance prototyping and research infrastructure develop clean well documented research codebases build experimentation frameworks and evaluation tooling contribute to shared training infrastructure and implement interfaces for broader robotics integration scientific leadership and publication drive an independent research agenda aligned with team objectives publish at top tier venues e g rss corl icra neurips identify research gaps through literature reviews and present findings via technical reports and talks cross functional collaboration partner with scientists engineers and leaders across teams to translate research into deployable solutions mentor junior researchers contribute to the team s scientific culture and support integration with robotics hardware teams a day in the life if you are not sure that every qualification on the list above describes you exactly we d still love to hear from you at amazon we value people with unique backgrounds experiences and skillsets if you re passionate about this role and want to make an impact on a global scale please apply about the team are you inspired by invention is problem solving through teamwork in your dna do you like the idea of seeing how your work impacts the bigger picture answer yes to any of these and you ll fit right in here at amazon robotics we are a smart collaborative team of enthusiastic doers that work passionately to apply innovative advances in robotics and software to solve real world challenges that will transform our customers experiences in ways we can t even image yet we invent new improvements every day we are amazon robotics and we will give you the tools and support you need to invent with us in ways that are rewarding fulfilling and fun applied scientist i amazon shipping in hr gurugram building large scale forecasting and optimization systems that power amazon s global transportation network and directly impact customer experience and cost key job responsibilities 1 guide model and system design across a range of techniques including tree based models deep learning lstms transformers llms and reinforcement learning 2 ensure models are production ready scalable and robust through close partnership with stakeholders 3 partner with product operations and engineering leaders to enable proactive decision making and corrective actions 4 own end to end business metrics directly influencing customer experience cost optimization and network reliability 5 help contribute to the broader ml community through publications conference submissions and internal knowledge sharing applied scientist prime video content reasoning enrichment localization us wa seattle prime video is a first stop entertainment destination offering customers a vast collection of premium programming in one app available across thousands of devices prime members can customize their viewing experience and find their favorite movies series documentaries and live sports including amazon mgm studios produced series and movies licensed fan favorites and programming from prime video subscriptions such as apple tv hbo max peacock crunchyroll and mgm all customers regardless of whether they have a prime membership or not can rent or buy titles via the prime video store and can enjoy even more content for free with ads are you interested in shaping the future of entertainment prime video s technology teams are creating best in class digital video experience as a prime video team member you ll have end to end ownership of the product user experience design and technology required to deliver state of the art experiences for our customers you ll get to work on projects that are fast paced challenging and varied you ll also be able to experiment with new possibilities take risks and collaborate with remarkable people we ll look for you to bring your diverse perspectives ideas and skill sets to make prime video even better for our customers with global opportunities for talented technologists you can decide where a career prime video tech takes you senior applied scientist real time conversational ai agi us ca sunnyvale we are looking for a senior applied scientist to help drive the research and development of real time multimodal conversational ai you will contribute across two focus areas advancing foundation models for speech and audio and building the post training systems reward modeling reinforcement learning that shape natural human like conversational behavior you will own a significant research area and contribute across the full model lifecycle from pre training and architecture design through post training alignment and real time deployment you will work at the frontier of what s possible in conversational ai with the compute data and runway to pursue problems that few teams in the world have the resources to tackle as a senior scientist you will drive the technical execution of your research area contribute to the team s roadmap and work closely with inference engineers to ensure your models are designed for real time production deployment key job responsibilities what you ll do foundation model scaling help build and train large scale multimodal foundation models for real time speech and audio generation from architecture design through production scale training advance the scaling and efficiency of conversational models including the relationship between data model size and real time performance design model architectures informed by hardware constraints and inference requirements working with inference engineers to ensure models are servable from inception develop training methodologies for multimodal models that jointly process and generate speech language and audio in real time streaming contexts contribute to the state of the art on efficient architectures and training methods for conversational ai at scale post training reinforcement learning design and build reward models and reward functions for speech systems capturing naturalness fluency conversational quality and real time responsiveness develop and apply reinforcement learning methods to shape conversational behavior teaching models natural timing responsiveness and fluid interaction build parts of the post training pipeline from sft through rl alignment optimized for real time multimodal outputs rather than text only generation design evaluation frameworks that capture the quality dimensions unique to real time conversation latency sensitivity audio quality prosody interaction naturalness real time perception generation advance the team s capabilities in real time perception the ability of the model to process incoming audio speech while simultaneously generating responses develop techniques for natural interactive systems where the model handles concurrent input and output with human like timing work at the intersection of model architecture and production constraints to ensure multimodal capabilities function within hard real time latency budgets 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 optimization we are looking for a senior applied scientist to tackle scientifically complex challenges in areas such as stochastic modeling queueing theory anomaly detection and optimization in this role you will design and deploy novel ml models and algorithms that directly improve how businesses interact with their customers you will work at the intersection of research and production turning ambiguous problems into scalable solutions that shape the future of cloud based customer service key job responsibilities design and deploy novel machine learning models and algorithms to solve complex problems in contact center operations including forecasting routing optimization and anomaly detection lead the scientific agenda for your team by identifying new research opportunities proposing initiatives and driving them from concept through production deployment collaborate with engineering teams to architect and implement scalable ml systems personally contributing significant portions of the critical scientific components mentor fellow scientists and engineers through code reviews design discussions and scientific guidance raising the overall technical bar of the team evaluate and advance the team s ml methodology by benchmarking against current academic and industry research and by publishing findings internally and externally when appropriate a day in the life you might start your morning reviewing experiment results from a new forecasting model then join a design session with engineers to discuss how to integrate it into the production pipeline after lunch you could be whiteboarding a novel approach to a queueing optimization problem with a fellow scientist followed by a code review for a teammate you will regularly present your research findings to stakeholders across the organization and contribute to the team s publication efforts about the team our team within amazon connect focuses on building intelligent ml driven capabilities that help businesses run their contact centers more effectively we work closely with product engineering and science partners to turn research ideas into features that customers rely on every day we value curiosity collaboration and scientific rigor and we are investing in new ai capabilities that will continue to transform the customer service industry if you want to see your research make a tangible impact at scale this is the place to do it sr applied scientist demandtech addelivery experience and measurement us ny new york want to work on building a amazon ads billion dollar business innovate on a new product and have a positive impact on millions of views while working with industry leading technologies we re growing a team to support the sponsored ads business that powers the advertising experience for millions of viewers and advertisers daily amazon is investing heavily in building a world class advertising business and developing a collection of self service performance advertising products that drive discovery and sales we deliver billions of ad impressions and millions of clicks daily and are constantly challenging ourselves to create world class products and an unparalleled shopping experience for our hundreds of millions of customers worldwide key job responsibilities we are building the next gen smart ads campaign at its core is an intelligence flywheel an architecture where every component s output is designed to train models that improve every other component the model layer that is meant to power every capability currently has no dedicated science ownership as the senior applied scientist on this team you own the science that makes the flywheel turn you will turn static threshold based logic into self improving closed loop intelligence and define the decision policies that let the system act autonomously with advertiser trust concretely you will build predictive issue detection models that identify under delivery over delivery and performance degradation from campaign signals before they materially impact advertisers design the intervention selection policy which autonomous action to take framed as a contextual bandit choose observe update engineers implement action execution you define the policy that selects actions establish causal attribution for autonomous optimization separating the effect of our interventions from organic performance change so improvements can be attributed and advertiser trust in autonomy can be earned integrate and adapt cross model signals combine creative quality product relevance and budget signals into a unified advertiser intelligence picture and adapt general purpose partner models to our product reality via fine tuning re ranking or thin adaptation layers close recommendation and grading feedback loops define reward schemas for accept reject and performance vs baseline signals correlate creative quality scores with real campaign outcomes and feed empirical findings back to both our product and partner science teams you will work backwards from ambiguous business problems set the science roadmap for the model layer and partner closely with the team s software engineers who own the services pipelines and execution infrastructure so that model artifacts you produce are deployed and served in production this is a high leverage high autonomy role your outputs are consumed by multiple engineering workstreams at once and you set the abstractions the team builds on about the team we are focused on goal oriented ai powered workflows that help advertisers achieve their marketing objectives we collect campaign goals surface relevant data at key decision points and provide reporting that validates decision making our product suite guides advertisers in building campaigns with optimal targeting creativ...
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