A child sits in a chair at a kitchen counter, wearing headphones while watching a Fire tablet
As children spend more hours in front of screens, it is increasingly important to investigate the effects of digital technology. Boston Children’s Hospital launched the Digital Wellness Lab, a research center providing science-based recommendations for parents and caretakers.

Amazon Kids links up with Boston Children’s Hospital’s Digital Wellness Lab

Science-based recommendations from the Digital Wellness Lab could inform the development of digital products that help children.

Parents worldwide are confronted with a similar question: What is the impact of screen time in the lives of their children?

As children spend more hours in front of screens, it becomes increasingly important to investigate the effects of digital technology on their brains, bodies, and behaviors.

To assist that effort, experts at Boston Children’s Hospital recently launched the Digital Wellness Lab, a research center providing practical, science-based recommendations for parents and caretakers on how to raise healthy children in the digital age.

Amazon Kids, one of the supporters of the initiative, provides free tools for parents to make choices about how their children interact with devices such as Amazon Fire tablets, Kindle e-readers, Echo smart speakers, and Fire TV.

The team says it hopes to utilize Digital Wellness Lab research as it continues to develop new products that help children explore quality content online while informing and empowering parents.

Officially launched in March, the Digital Wellness Lab is an evolution of the Center on Media and Child Health at Boston Children's Hospital, which had been investigating the impact of media use on children’s mental and physical health for almost 20 years.

Michael Rich and David Bickham
Michael Rich, left, is the founder and director of the Digital Wellness Lab. David Bickham, right, is the lab's research scientist lead.
Glynis Condon

For the past couple of decades, the amount and the quality of research in this field has increased significantly, but its results remained mostly restricted to academia.

“It struck me that, no matter how wonderful our research was, until we got it into the hands of the people who could actually change the digital environment, we were going to be spinning our wheels,” said pediatrician Michael Rich, the lab’s founder and director.

He notes that while the tech industry is highly competitive, this is a topic where companies are collaborating to address the common concern over impact of technology on children. The Digital Wellness Lab originated from the idea that, by working together with industry, science could foster real change in devices, platforms, and software in ways to promote the wellness of individuals and society.

Amazon Kids’ support for science

Karen Ressmeyer, Amazon Kids director of Family Trust, describes the alliance with the Digital Wellness Lab as a win-win situation.

“This collaboration provides us with new insights and data from the lab to help our mission of contributing to a positive digital environment,” she said.

The goal of Amazon Kids and Amazon Kids+ — a subscription service providing access to thousands of books, movies, TV shows, and educational curated content — is to give children the freedom to explore high-quality content in a kid-friendly environment within parameters set by their parents or caretakers.

Karen Ressmeyer, left, is Amazon Kids director of Family Trust. Catherine Teitelbaum, right,
Karen Ressmeyer, left, is Amazon Kids director of Family Trust. Catherine Teitelbaum, right, is principal, Family Trust at Amazon Kids.
Glynis Condon

Working with the Digital Wellness Lab furthers that goal in a unique fashion, according to Catherine Teitelbaum, principal, Family Trust at Amazon Kids. “With this partnership we are intentionally creating a forum to discuss ideas of all sizes and learn from researchers, academics, and clinicians as we look to constantly strengthen our commitment to the wellness of kids and families,” she said.

While tech companies like Amazon can conduct research on their own to address concerns about the impact of technology on children’s mental health, this arrangement offers the ability to develop fundamental research that is completely independent and agnostic to outcomes, noted Rich.

“Our goal is to offer a resource that can inform both sides of the paradigm — the producers and the consumers — to move what they create and what they consume toward a better place in terms of physical, mental and social health,” he said.

Investigating how technology affects children

At the moment, one of the main research questions related to wellness and technology is how the COVID-19 pandemic has changed the use of technology by children.

One of the first efforts by the Digital Wellness Lab was a national survey with parents of children from kindergarten to grade 12 that showed as kids’ media use increased during the pandemic, so did the frequency of arguments with their parents over that usage. However, the survey found that spike did not owe purely to kids streaming videos.

“We also found that over 70% of children were using these devices to connect with their family and their friends, and this was true across all age groups,” said David Bickham, research scientist lead at the Digital Wellness Lab. When asked if media use was helpful or hurtful for their children, more than half of the parents said it was helpful for their social relationships and educational achievements.

That more nuanced understanding is a departure from the historically high degree of polarization around this topic, Rich observed. “You were either for kids or for screens, but you couldn't be for both,” he said. Having had an earlier career as a screenwriter and filmmaker – which included working as assistant director to Akira Kurosawa in Japan – he knew that people who were making media were not out to hurt kids.

Bickham noted that, rather than trying to label whether media use is fundamentally good or bad, the lab is trying to identify these types of nuances.

Open research questions

Historically, this field of research hasn’t determined clear causal relationships between types of screen use and mental and physical health outcomes, which constitutes an important gap, according to Rich.

What we want to do is start to move from correlations to understanding what type of screen use contributes to which outcomes.
Michael Rich

“For example, we don't know whether playing violent video games makes kids more violent, or whether more violent kids are drawn to violent video games,” he explained. “We just see correlations, and what we want to do is start to move from correlations to understanding what type of screen use contributes to which outcomes.”

The way to get there, notes Rich, is through long-term longitudinal studies, a type of research that follows the subjects for several years and collects data on different variables periodically. The Digital Wellness Lab has a project to do exactly that. The Growing Up Digital project is a 10-year longitudinal study that plans to have at least one site in each of the six populated continents.

“We are going to follow two cohorts of children, from preschool to middle school, and from middle school to young adulthood, on an annual basis measuring in a deep way not just the screens they are actively using, but also those they are ambiently exposed to,” Rich noted.

The study will measure several outcomes related to learning, mental health, and physical health, such as sleep, exercise and nutrition.

The program is already underway in Australia and Canada, and the group is having conversations with institutions from countries like India and Brazil to set up the study in those geographies as well.

bchimage.png
The Digital Wellness Lab is an evolution of the Center on Media and Child Health at Boston Children's Hospital.
Courtesy of Boston Children's Hospital

The lab also hopes to look at how the use of technology differs across cultures. Previous work by the group looked into digital media usage and play in young children from the United States and Mexico. While, in the U.S., “media use may have displaced time dedicated to certain types of play,” the opposite was true in Mexico: “play seemed to facilitate or positively co-occur with media use.”

“When you think about not just the amount of time spent with screens, but the characteristics of technology use and cultural differences, you start to reveal a more nuanced understanding of how technology impacts kids and their development,” Bickham said.

According to Rich, researchers in this field are coming to realize that it's not about the total duration of screen use, but what we are doing on the screens and the context in which we are doing it. In order to empower families to evaluate what type of technology use is healthy for their children, the lab recently published the Family Digital Wellness Guide, which gives science-based practical advice on the topic for parents and caretakers.

Empowering families is also one of the main goals of Amazon Kids.

“That is so closely tied with our focus at Amazon Kids,” said Teitelbaum, “where we have a long history of building not just products that are safe for kids and designed for kids, but engaging with parents through our parent dashboard, providing them choices to shape their children’s use of media.”

Related content

AU, VIC, Melbourne
Are you excited about leveraging state-of-the-art Computer Vision algorithms and large datasets to solve real-world problems? Join Amazon as an Applied Scientist Intern and be at the forefront of AI innovation! As an Applied Scientist Intern, you'll work in a fast-paced, cross-disciplinary team of pioneering researchers. You'll tackle complex problems, developing solutions that either build on existing academic and industrial research or stem from your own innovative thinking. Your work may even find its way into customer-facing products, making a real-world impact. Please note: This internship is a duration of 6 months full time with a start date in Jan-March 2027. The successful intern is required to be based in Melbourne and relocation allowance will be provided if you are based outside of Melbourne. Key job responsibilities - Develop novel solutions and build prototypes - Work on complex problems in Computer Vision and Machine Learning - Contribute to research that could significantly impact Amazon's operations - Collaborate with a diverse team of experts in a fast-paced environment - Collaborate with scientists on writing and submitting papers to Tier-1 conferences (e.g., CVPR, ICCV, NeurIPS, ICML) - Present your research findings to both technical and non-technical audiences Key Opportunities - Collaborate with leading machine learning researchers - Access Amazon tools and hardware (large GPU clusters) - Address challenges at an unparalleled scale - Become a disruptor, innovator, and problem solver in the field of computer vision - Potentially deliver solutions to production in customer-facing applications - Opportunities to become an FTE after the internship Join us in shaping the future of AI at Amazon. Apply now and turn your research into real-world solutions!
US, CA, Pasadena
The Amazon Web Services (AWS) Center for Quantum Computing in Pasadena, CA, is looking to hire a Research Scientist with experience in semiconductor process development who will aid in AWS’s effort to bring cloud quantum computing services to its worldwide customer base. You will join a multi-disciplinary team of scientists, and hardware and software engineers working at the forefront of quantum computing. Through your work inside and outside of the cleanroom environment in the fabrication research and development group, you will solve problems related to developing next-generation quantum processors. Candidates must have a demonstrated background in sound scientific and engineering principles, and must have excellent data analysis, bias for action, problem solving, and communication skills, and be highly motivated and curious to research and learn new technical topics as needed. As a research scientist you will be expected to work on new ideas and stay abreast of novel approaches in fabricating and packaging superconducting quantum processors. Working effectively within a team environment is critical. Key job responsibilities Responsibilities include developing novel processes to fabricate high-coherence superconducting qubits; developing advanced 3DI interconnect and routing technologies for integrating superconducting quantum technologies; analyzing inline metrology and electrical test data; writing production standard operating procedures to transfer newly-developed processes to production teams; interacting with project leads to provide feedback that continuously improves different processes. A day in the life The candidate will develop novel technologies using micro-/nano-fabrication techniques inside the cleanroom (independently or in collaboration with other scientists and engineers) for next-generation quantum computing. Outside the cleanroom, the candidate will plan experiments, analyze data, and conceive future innovations. About the team AWS Utility Computing (UC) provides product innovations — from foundational services such as Amazon’s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS’s services and features apart in the industry. As a member of the UC organization, you’ll support the development and management of Compute, Database, Storage, Internet of Things (Iot), Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for their cloud services. Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the 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. Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. 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 (diversity) conferences, inspire us to never stop embracing our uniqueness. 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. Hybrid Work We value innovation and recognize this sometimes requires uninterrupted time to focus on a build. We also value in-person collaboration and time spent face-to-face. Our team affords employees options to work in the office every day or in a flexible, hybrid work model near one of our U.S. Amazon offices.
US, WA, Redmond
We are searching for a talented candidate with expertise in orbital mechanics and spaceflight navigation, including LEO Satellite Orbit Determination. This position requires experience in simulation and analysis of spacecraft orbital mechanics and sequential orbit determination methods, including Extended Kalman Filters (EKF) and/or Unscented Kalman Filter (UKF). Strong analysis skills are required to develop engineering studies of complex large-scale dynamical systems. This position requires demonstrated expertise in computational analysis automation and tool development. Key job responsibilities - Perform spacecraft maneuver or navigation analysis in support of multi-disciplinary trades within the Amazon Leo team. - Contribute to prototype software development of flight algorithms. - Test and assess navigation software for integration into flight systems. - Assess and trouble-shoot the performance of Leo on-board GNSS hardware and software systems. - Work closely with GNC engineers to manage on-orbit performance and develop flight dynamics operations processes. Export Control Requirement: Due to applicable export control laws and regulations, candidates must be 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. A day in the life - Interacting with GNC teams to evaluate and troubleshoot satellite issues. - Working within the Flight Dynamics Research team to prioritize tasks. - Performing analysis, simulation, testing and documentation to address assigned tasks.
IN, KA, Bengaluru
Are you passionate about solving complex business problems at scale through Generative AI? Do you want to help build intelligent systems that reason, act, and learn from minimal supervision? If so, we have an exciting opportunity for you on Amazon's Trustworthy Shopping Experience (TSE) team. At TSE, our vision is to guarantee customers a worry-free shopping experience by earning their trust that the products they buy are safe, authentic, and compliant with regulations and policy. We do this in close partnership with our selling partners, empowering them with best-in-class tools and expertise to offer a high-quality, compliant selection that customers trust. As an Applied Scientist I, you will bring subject matter expertise in at least one relevant discipline (e.g., NLP, computer vision, representation learning, agentic architecture) to contribute to next-generation agentic AI solutions that automate complex manual investigation processes at Amazon scale. Working alongside senior scientists, you will map business goals—such as reducing cost-of-serving while maintaining trust and safety standards—to well-defined scientific problems and metrics. You will invent, refine, and experiment with solutions spanning agentic reasoning, self-supervised representation learning, few-shot adaptation, multimodal understanding, and model compression. With guidance from senior scientists, you will stay current on research trends and benchmark your results against the state of the art. You will help design and execute experiments to identify optimal solutions, initiating the development and implementation of small components with team guidance. You will write secure, stable, testable, and well-documented production code at the level of an SDE I, rigorously evaluating models and quantifying performance. You will handle data in accordance with Amazon policies, troubleshoot issues to root cause, and ensure your work does not put the company at risk. Your scope of influence will typically be at the self-level, with the possibility of mentoring interns. You will participate in team design and prioritization discussions, learn the business context behind TSE's products, and escalate problems with proposed solutions. You will publish internal technical reports and may contribute to peer-reviewed publications and external review activities when aligned with business needs. This role offers a unique opportunity to contribute to end-to-end AI development—from research through production—with your contributions serving hundreds of millions of customers within months, not years. Key job responsibilities • Contribute to the design and development of agentic AI systems with multi-step reasoning, autonomous task execution, and multimodal intelligence, including feedback and memory mechanisms, leveraging reinforcement learning techniques for agent decision-making and policy optimization, with input and guidance from senior scientists • Help productionize models built on top of SFT (Supervised Fine-tuning) and RFT (Reinforced Fine-tuning) approaches, as well as few-shot approaches based on multimodal datasets spanning text, images, and structured data, applying mathematical optimization techniques to improve efficiency, resource allocation, and decision-making in complex workflows, working alongside senior scientists to identify optimal solutions • Contribute to building production-ready deep learning and conventional ML solutions, including multimodal fusion and cross-modal alignment techniques that seamlessly connect visual, textual, and relational understanding, to support automation requirements within your team's scope • Help identify customer and business problems; use reasonable assumptions, data, and customer requirements to solve well-defined scientific problems involving multimodal inputs such as unstructured text, documents, product images, and relational data, developing representations that capture complementary signals across modalities and mapping business goals to scientific metrics • May co-author research papers for peer-reviewed internal and/or external venues, including contributions in areas such as multimodal representation learning and vision-language modeling, and contribute to the wider scientific community by reviewing research submissions, when aligned with business needs • Prototype rapidly, iterate based on feedback, and deliver small components at SDE I level—including multimodal data pipelines and inference modules—that integrate into production-scale systems • Write secure, stable, testable, maintainable, and well-documented code, balancing model capability, deployment cost, and resource usage across multimodal architectures while understanding state-of-the-art data structures, algorithms, and performance tradeoffs • Rigorously test code and evaluate models across individual and combined modalities, quantifying their performance; troubleshoot issues, research root causes, and thoroughly resolve defects, leaving systems more maintainable • Participate in team design, scoping, and prioritization discussions through clear verbal and written communication; seek to learn the business context, science, and engineering behind your team's products, including how multimodal signals contribute to trust and safety decisions • Participate in engineering best practices with peer reviews; clearly document approaches and communicate design decisions; publish internal technical reports to institutionalize scientific learning • Help train and mentor scientist interns; identify and escalate problems with proposed solutions, taking ownership or ensuring clear hand-off to the right owner About the team Trustworthy Shopping Experience Product team in TSE is responsible for the human-in-the-loop products and technology used in the risk investigations at Amazon. The team is also responsible for reducing the cost of performing the investigations, by automating wherever possible and optimizing the experience where manual interventions are needed. The team leverages state-of-the art technology and GenAI to deliver the products and associated goals.
IN, KA, Bengaluru
The Trust CX Innovations team is looking for an Applied Scientist with strong background in Generative AI space to build solutions that help in upholding customer trust for Alexa+. As an Applied Scientist in Trust CX innovations, you will be at the forefront of developing innovative solutions to critical challenges in AI trust and privacy. You'll lead research in trust-preserving machine learning techniques. We are working on revolutionizing the way Amazonians work and collaborate. You will help us achieve new heights of productivity through the power of advanced generative AI technologies. Key job responsibilities - Lead research initiatives in generative AI, focusing on LLMs, multimodal models, and frontier AI capabilities - Develop innovative approaches for model optimization, including prompt engineering, few-shot learning, and efficient fine-tuning - Pioneer new methods for AI safety, alignment, and responsible AI development - Design and execute sophisticated experiments to evaluate model performance and behavior - Lead the development of production-ready AI solutions that scale efficiently - Collaborate with product teams to translate research innovations into practical applications - Guide engineering teams in implementing AI models and systems at scale - Author technical papers for top-tier conferences - File patents for novel AI technologies and applications A day in the life You will be working with a group of talented scientists on researching algorithm and running experiments to test scientific proposal/solutions to improve our trust-preserving experiences. This will involve collaboration with partner teams including engineering, PMs, data annotators, and other scientists to discuss data quality, policy, and model development. You work closely with partner teams across Alexa to deliver platform features that require cross-team leadership. About the team Who We Are: Trust CX Innovations is a strategic innovation team within Amazon Devices & Services that focuses on advancing AI technology while prioritizing customer trust and experience. Our team operates at the intersection of artificial intelligence, privacy engineering and customer-centric design. Our Mission: To pioneer trustworthy AI innovations that delight customers while setting new standards for privacy and responsible technology development. We aim to transform how Amazon builds AI products by creating solutions that balance innovation with customer trust.
GB, Cambridge
Alexa is looking for an Applied Scientist with a strong background in Natural Language Processing (NLP) and Large Language Models (LLMs) to help build state-of-the-art conversational systems. In this role, you will collaborate with a large team of scientists training the Large Language Models that power the Alexa stack, as well as software engineers serving them in production systems. You will own solutions end-to-end: from ideation and research through to production deployment, enabling conversational assistants to support external tools, leverage diverse sources of information, and deliver novel reasoning capabilities to millions of Alexa customers. Key job responsibilities As an Applied Scientist, you will develop innovative solutions to complex problems to extend the functionalities of conversational assistants. You will use your technical expertise to research and implement novel algorithms and modelling solutions in collaboration with other scientists and engineers. You will analyze customer behaviors and define metrics to enable the identification of actionable insights and measure improvements in customer experience. You will communicate results and insights to both technical and non-technical audiences through written reports, presentations and external publications. You would be able to bi-modal on science and engineering: someone who combines strong scientific foundations with the execution skills to ship high-quality solutions. A day in the life As an Applied Scientist on the Alexa Science team, you'll drive innovation in evaluating new product experiences while discovering novel approaches to enhance model capabilities and enrich customer interactions. You'll collaborate with cross-functional teams of engineers and scientists to identify root causes of model and system integration issues, continuously improving the end-to-end customer experience. You'll partner closely with scientists developing and fine-tuning large language models, engineers building low-latency inference infrastructure, and product teams defining customer experience metrics. About the team We are a team of applied scientists and engineers building the intelligence layer that powers Alexa+. Our work sits at the intersection of large language models, decision-making under uncertainty, and production ML systems. What we build directly shapes the customer experience: determining which models serve their requests, optimizing response latency, and creating natural, seamless interactions. We're a collaborative team that values rigorous experimentation, clear communication, and delivering solutions that perform at scale in real-world environments.
IN, KA, Bengaluru
Do you want to join an innovative team of scientists who use machine learning and statistical techniques to create state-of-the-art solutions for providing better value to Amazon’s customers? Do you want to build and deploy advanced ML systems that help optimize millions of transactions every day? Are you excited by the prospect of analyzing and modeling terabytes of data to solve real-world problems? Do you like to own end-to-end business problems/metrics and directly impact the profitability of the company? Do you like to innovate and simplify? If yes, then you may be a great fit to join the Machine Learning team for India Consumer Businesses. Machine Learning, Big Data and related quantitative sciences have been strategic to Amazon from the early years. Amazon has been a pioneer in areas such as recommendation engines, ecommerce fraud detection and large-scale optimization of fulfillment center operations. As Amazon has rapidly grown and diversified, the opportunity for applying machine learning has exploded. We have a very broad collection of practical problems where machine learning systems can dramatically improve the customer experience, reduce cost, and drive speed and automation. These include product bundle recommendations for millions of products, safeguarding financial transactions across by building the risk models, improving catalog quality via extracting product attribute values from structured/unstructured data for millions of products, enhancing address quality by powering customer suggestions We are developing state-of-the-art machine learning solutions to accelerate the Amazon India growth story. Amazon India is an exciting place to be at for a machine learning practitioner. We have the eagerness of a fresh startup to absorb machine learning solutions, and the scale of a mature firm to help support their development at the same time. As part of the India Machine Learning team, you will get to work alongside brilliant minds motivated to solve real-world machine learning problems that make a difference to millions of our customers. We encourage thought leadership and blue ocean thinking in ML. Key job responsibilities Use machine learning and analytical techniques to create scalable solutions for business problems Analyze and extract relevant information from large amounts of Amazon’s historical business data to help automate and optimize key processes Design, develop, evaluate and deploy, innovative and highly scalable ML models Work closely with software engineering teams to drive real-time model implementations Work closely with business partners to identify problems and propose machine learning solutions Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model maintenance Work proactively with engineering teams and product managers to evangelize new algorithms and drive the implementation of large-scale complex ML models in production Leading projects and mentoring other scientists, engineers in the use of ML techniques About the team International Machine Learning Team is responsible for building novel ML solutions that attack India first (and other Emerging Markets across MENA and LatAm) problems and impact the bottom-line and top-line of India business. Learn more about our team from https://www.amazon.science/working-at-amazon/how-rajeev-rastogis-machine-learning-team-in-india-develops-innovations-for-customers-worldwide
US, CA, San Francisco
Amazon is on a mission to redefine the future of automation — and we're looking for exceptional talent to help lead the way. We are building the next generation of advanced robotic systems that seamlessly blend cutting-edge AI, sophisticated control systems, and novel mechanical design to create adaptable, intelligent automation solutions capable of operating safely alongside humans in dynamic, real-world environments. At Amazon, we leverage the power of machine learning, artificial intelligence, and advanced robotics to solve some of the most complex operational challenges at a scale unlike anywhere else in the world. Our fleet of robots spans hundreds of facilities globally, working in sophisticated coordination to deliver on our promise of customer excellence — and we're just getting started. As a Applied Scientist in Robot Perception, you will be at the forefront of this transformation. You will develop and deploy state-of-the-art perception algorithms that enable robots to truly understand and interact with the physical world — bridging the gap between theoretical research and real-world impact. Bringing deep expertise in Computer Vision and a nuanced understanding of the capabilities and limitations of modern Vision-Language Models (VLMs), you will innovate boldly and push the boundaries of what's possible. Our vision for the Perception layer is ambitious: to enable seamless, intelligent interaction between the user, the robot, and its environment. This is a rare opportunity to work at the intersection of deep learning, large language models, and robotics — contributing to research that doesn't just advance the field, but reshapes it. You will collaborate with world-class teams pioneering breakthroughs in dexterous manipulation, locomotion, and human-robot interaction, all at an unprecedented scale. Join us in building intelligent robotic systems that will define the future of automation and human-robot collaboration. Key job responsibilities - Design, develop, and deploy perception algorithms for robotics systems, including object detection, segmentation, tracking, depth estimation, and scene understanding - Lead research initiatives in computer vision, sensor fusion and 3D perception - Collaborate with cross-functional teams including robotics engineers, software engineers, and product managers to define and deliver perception capabilities - Drive end-to-end ownership of ML models — from data collection and labeling strategy to training, evaluation, and deployment - Mentor junior scientists and engineers; contribute to a culture of technical excellence - Define and track key metrics to measure perception system performance in real-world environments - Publish research findings in top-tier venues (CVPR, ICCV, ECCV, ICRA, NeurIPS, etc.) and contribute to patents A day in the life - Train ML models for deployment in simulation and real-world robots, identify and document their limitations post-deployment - Drive technical discussions within your team and with key stakeholders to develop innovative solutions to address identified limitations - Actively contribute to brainstorming sessions on adjacent topics, bringing fresh perspectives that help peers grow and succeed — and in doing so, build lasting trust across the team - Mentor team members while maintaining significant hands-on contribution to technical solutions
US, NY, New York
The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights. We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising. We are seeking a technical leader for our Supply Science team. This team is within the Sponsored Product team, and works on complex engineering, optimization, econometric, and user-experience problems in order to deliver relevant product ads on Amazon search and detail pages world-wide. The team operates with the dual objective of enhancing the experience of Amazon shoppers and enabling the monetization of our online and mobile page properties. Our work spans ML and Data science across predictive modeling, reinforcement learning (Bandits), adaptive experimentation, causal inference, data engineering. Key job responsibilities Search Supply and Experiences, within Sponsored Products, is seeking a Senior Applied Scientist to join a fast growing team with the mandate of creating new ads experience that elevates the shopping experience for our hundreds of millions customers worldwide. We are looking for a top analytical mind capable of understanding our complex ecosystem of advertisers participating in a pay-per-click model– and leveraging this knowledge to help turn the flywheel of the business. As a Senior Applied Scientist on this team you will: --Act as the technical leader in Machine Learning and drive full life-cycle Machine Learning projects. --Lead technical efforts within this team and across other teams. --Build machine learning models, perform proof-of-concept, experiment, optimize, and deploy your models into production. --Run A/B experiments, gather data, and perform statistical analysis. --Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving. --Work closely with software engineers to assist in productionizing your ML models. --Research new machine learning approaches. --Recruit Applied Scientists to the team and act as a mentor to other scientists on the team. A day in the life The successful candidate will be a self-starter comfortable with ambiguity, with strong attention to detail, and with an ability to work in a fast-paced, high-energy and ever-changing environment. The drive and capability to shape the direction is a must. About the team We are a customer-obsessed team of engineers, technologists, product leaders, and scientists. We are focused on continuous exploration of contexts and creatives where advertising delivers value to customers and advertisers. We specifically work on new ads experiences globally with the goal of helping shoppers make the most informed purchase decision. We obsess about our customers and we are continuously innovating on their behalf to enrich their shopping experience on Amazon
IN, KA, Bengaluru
The Seller Fee Science Team integrates economic modeling, machine learning, and artificial intelligence to guide fee strategy, quantify its impact, and ensure fees are accurately computed and explained for billions of transactions between Amazon selling partners and customers. We help build the foundations for growing selling partner businesses, bringing the best selection and prices to Amazon customers, and helping Amazon leaders make and implement high impact decisions that optimally balance profitability and growth. Our team brings together world-class economists, physicists, mathematicians, and computer scientists to tackle diverse challenging problems that require theoretical rigor and deliver real-world impact. As an data scientist on our team, this role will focus on the application of data analysis, econometrics, machine learning, and artificial intelligence to measure and predict Amazon's P&L, with emphasis on fee revenue. This blends the tools of data science, statistics, and ML/AI. Your work will shape not only how fees are decided, but how they are interpreted and planned. We are seeking scientists who are motivated by first principles, disciplined experimentation, and the technical challenge of deploying ideas at global scale. This is an opportunity to work on consequential problems where analytic rigor meets real-world complexity, and where your analysis, models, algorithms, and systems will directly influence the experience of millions of sellers. If you are driven to build elegant solutions to hard problems—and to see them operate in production at meaningful scale—we would welcome the opportunity to build with you. Key job responsibilities ** Translate ambiguous business challenges into well-defined scientific problems with measurable impact. ** Identify opportunities to improve fee revenue measurement, prediction, planning, structure, and level. ** Identify opportunities to improve measurement, and prediction of other items of the P&L, at appropriate levels of granularity. ** Design, develop, and deploy econometric or AI/ML models that improve our understanding of the relationship between fees and costs, or predict fee revenue, and other elements of the P&L. ** Partner closely with finance and fee strategy teams to formulate scientific questions, communicate results, and productionalize solutions. **Apply rigorous simulation methods to validate models and quantify business impact at scale. **Communicate scientific innovations and results clearly to cross-functional stakeholders and contribute to the broader internal and external scientific community through publications, talks, and technical artifacts. About the team Amazon’s third-party marketplace is a multibillion-dollar global service, connecting customers and sellers across through billions of transactions annually. The Seller Fee Science Team integrates economic modeling, machine learning, and artificial intelligence to guide business fee strategy, ensure fees are accurately computed for millions of products, and improve the seller experience with AI tools that support any fee related contact (understanding, audit, and dispute). We build the scientific foundation that empowers sellers to grow their businesses with clarity and confidence. Our team brings together world-class economists, physicists, mathematicians, and computer scientists to tackle diverse challenging problems that require theoretical rigor and deliver real-world impact.