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

BR, SP, Sao Paulo
Do you like working on projects that are highly visible and are tied closely to Amazon’s growth? Are you seeking an environment where you can drive innovation leveraging the scalability and innovation with Amazon's AWS cloud services? The Amazon IESP Digital Payments & Emerging Team is hiring Applied Scientists to work in our Machine Learning team in São Paulo, Brazil. The Payments team designs and builds scalable payment systems that power Amazon's checkout and financial services across emerging countries (Brazil, Mexico, Australia, Singapore, and more). We tackle complex challenges in payment orchestration, fraud detection, and regional payment method integration to drive conversion and deliver seamless experiences at scale. Key job responsibilities About you You want to make changes that help millions of customers. You don’t want to make something 10% better as a part of an enormous team. Rather, you want to innovate with a small community of passionate peers. You have experience in analytics, machine learning, LLMs and Agentic AI, and a desire to learn more about these subjects. You want a trusted role in strategy and product design. You put the customer first in your thinking. You have great problem solving skills. You research the latest data technologies and use them to help you innovate and keep costs low. You have great judgment and communication skills, and a history of delivering results. Your Responsibilities - Define and own complex machine learning solutions in the consumer space, including targeting, measurement, creative optimization, and multivariate testing. - Design, implement, and evolve Agentic AI systems that can autonomously perceive their environment, reason about context, and take actions across business workflows—while ensuring human-in-the-loop oversight for high-stakes decisions. - Influence the broader team's approach to integrating machine learning into business workflows. - Advise leadership, both tech and non-tech. - Support technical trade-offs between short-term needs and long-term goals.
US, NY, New York
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! Key job responsibilities • Build generative AI models that create production-ready content, including movie content, localized assets, and visual marketing materials used across Prime Video's global platform. • Drive end-to-end machine learning projects that have a high degree of ambiguity, scale, complexity. • Build machine learning models, perform proof-of-concept, experiment, optimize, and deploy your models. • Run 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. • Research new and innovative machine learning approaches. • Share knowledge and research outcomes via internal and external conferences and journal publications A day in the life Prime Video is pioneering the use of Generative AI to empower the next generation of creatives. Our mission is to make world-class media creation accessible, scalable, and efficient. We are seeking an Applied Scientist to advance the state of the art in Generative AI and to deliver these innovations as production-ready systems at Amazon scale. Your work will give creators unprecedented freedom and control while driving new efficiencies across Prime Video’s global content and marketing pipelines. This is a newly formed team within Prime Video Science!
ES, M, Madrid
Are you interested in building the measurement foundation that proves whether targeted, cohort-based marketing actually changes customer behavior at Amazon scale? We are seeking an Applied Scientist to own measurement and experimentation for our Lifecycle Marketing Experimentation roadmap within the PRIMAS (Prime & Marketing Analytics and Science) team. In this role, you will design and execute rigorous experiments that measure the effectiveness of audience-based marketing campaigns across multiple channels, providing the evidence that guides marketing strategy and investment decisions. This is a high-impact role where you will build measurement frameworks from scratch, design experiments that isolate causal effects, and establish the experimental standards for lifecycle marketing across EU. You will work closely with business leaders and the senior science lead to answer critical questions: does targeting specific cohorts (Bargain hunters, Young adults) improve efficiency vs. broad campaigns? Which creative strategies drive behavior change? How should we optimize marketing spend across channels? Key job responsibilities Measurement & Experimentation Ownership: 1. Own measurement end-to-end for lifecycle marketing campaigns – design experiments (RCTs, geo-tests, audience holdouts) that measure campaign effectiveness across marketing channels 2. Build measurement frameworks and experimental best practices that work across different activation platforms and can scale to multiple campaigns 3. Establish experimental standards and tooling for lifecycle marketing, ensuring statistical rigor while balancing business constraints Causal Inference & Analysis: 1. Apply causal inference methods to measure incremental impact of marketing campaigns vs. counterfactual 2. Navigate measurement challenges across different platforms (Meta attribution, LiveRamp, clean rooms, onsite tracking) 3. Analyze experiment results and provide optimization recommendations based on statistical evidence 4. Establish guardrails and success criteria for campaign evaluation About the team The PRIMAS team, is part of a larger tech tech team called WIMSI (WW Integrated Marketing Systems and Intelligence). WIMSI core mission is to accelerate marketing technology capabilities that enable de-averaged customer experiences across the marketing funnel: awareness, consideration, and conversion.
US, MA, N.reading
As an Applied Scientist on the Science SW team, you will collaborate closely with other scientists and engineers to bring Reinforcement Learning (RL) research to production. This role combines the scientific application of ML, and specifically RL and sequential decision making, with software development engineering and a strong product focus. It will be your job to design, implement, and deploy novel RL agents, reward models, and control policies in both prototype and production environments, and to prove their impact in high-fidelity simulation before scaling them across the fleet. Key job responsibilities • Own the research and development of reinforcement learning and sequential decision making solutions spanning deep RL, policy optimization, offline/batch RL, contextual bandits, and multi-agent RL for real-time MHE control and building-wide optimization in a production environment. • Formulate fulfillment operations problems (throughput optimization, flow, merge, and congestion control) as sequential decision-making problems, and design multi-objective reward functions that balance competing operational objectives. • Build and leverage high-fidelity simulation environments for safe offline training, policy validation, and sim-to-real transfer before fleet-scale deployment. • Collaborate across multiple science and engineering teams to integrate RL policies into real-time production and control systems. About the team Amazon is building next generation software, hardware, and processes that will run our global network of fulfillment centers that move millions of units of inventory, and ensure customers get what they want when promised. The Science Software team in the One MHS organization unlocks Material Handling Equipment (MHE) innovation through a multiplicity of disciplines within Artificial Intelligence (AI) and applied science, including Computer Vision (CV), Physics-Informed Neural Networks (PINNs), Optimization, Reinforcement Learning, classical Machine Learning, statistical modeling, and sensing-hardware prototyping. Rooted in first principles aligned experimentation, the team is dedicated to building self-optimizing fulfillment centers, developing the models that drive real-time, building-wide orchestration of MHE. We conduct experiments, develop models, and apply machine learning (ML) at scale to optimize throughput, flow, merge, and congestion control, and to improve operational performance across the fulfillment network.
US, WA, Bellevue
Amazon Leo is Amazon’s low Earth orbit satellite broadband network. Its mission is to deliver fast, reliable internet to customers and communities around the world, and we’ve designed the system with the capacity, flexibility, and performance to serve a wide range of customers, from individual households to schools, hospitals, businesses, government agencies, and other organizations operating in locations without reliable connectivity. 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. As a Senior Data Scientist (DS), you will drive the development and implementation of advanced analytics and machine learning solutions. You will work on critical initiatives including natural language processing for non-conformance analysis, statistical process controls (SPC) for test optimization, and equipment predictive maintenance models to enable manufacturing rate acceleration. Your work will directly influence Kuiper’s production manufacturing workflow. You are an analytical problem solver who enjoys diving into data from various businesses, is excited about investigations and algorithms, can multi-task, and can credibly interface between scientists, engineers, and business stakeholders. Your expertise in synthesizing and communicating insights and recommendations to audiences of varying levels of technical sophistication will enable you to answer specific business questions and innovate for the future. Key job responsibilities Lead the design and implementation of ML/LLM solutions to analyze manufacturing data and identify failure patterns and operational risks Design predictive models for statistical process control and equipment maintenance optimization Build production-ready ML pipelines leveraging AWS services (e.g., SageMaker, Bedrock, AWS Glue) Formalize assumptions about how models are expected to behave, creating definitions of outliers, developing methods to systematically identify these outliers, and explaining why they are reasonable or identifying fixes for them Develop and test model enhancements, running computational experiments, and fine-tuning model parameters for new models Collaborate with engineering teams to translate complex manufacturing challenges into data-driven solutions Drive consensus on metrics and analysis approaches to support business strategy Write documents and create compelling visualizations and presentations to communicate insights to stakeholders Mentor team members and drive data science best practices across the organization About the team Established in 2023 as ProdOps was preparing to transition from development into full-rate production, OCC was purpose-built to ensure that as manufacturing scaled, the most critical problems would be identified, solved, and prevented from recurring through a single integrated operating system. OCC focuses on the most critical problems for ProdOps at each phase of production. The team operates as a closed-loop flywheel where each rotation identifies value, solves problems, implements change, and generates new data that feeds the next cycle. Every rotation compounds returns.
US, CA, Sunnyvale
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 add-on subscriptions such as Apple TV+, Max, 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 technologist, 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! We are looking for a self-motivated, passionate and resourceful Applied Scientist to bring diverse perspectives, ideas, and skill-sets to make Prime Video even better for our customers. You will spend your time as a hands-on machine learning practitioner and a research leader. You will play a key role on the team, building and guiding machine learning models from the ground up. At the end of the day, you will have the reward of seeing your contributions benefit millions of Amazon.com customers worldwide. Key job responsibilities - Develop AI solutions for various Prime Video Search systems using Deep learning, GenAI, Reinforcement Learning, and optimization methods; - Work closely with engineers and product managers to design, implement and launch AI solutions end-to-end; - Design and conduct offline and online (A/B) experiments to evaluate proposed solutions based on in-depth data analyses; - Effectively communicate technical and non-technical ideas with teammates and stakeholders; - Stay up-to-date with advancements and the latest modeling techniques in the field; - Publish your research findings in top conferences and journals. About the team Prime Video Search Science team owns science solution to power search experience on various devices, from sourcing, relevance, ranking, to name a few. We work closely with the engineering teams to launch our solutions in production.
US, NY, New York
We are seeking an Applied Scientist to lead the development of evaluation frameworks and data collection protocols for robotic capabilities. In this role, you will focus on designing how we measure, stress-test, and improve robot behavior across a wide range of real-world tasks. Your work will play a critical role in shaping how policies are validated and how high-quality datasets are generated to accelerate system performance. You will operate at the intersection of robotics, machine learning, and human-in-the-loop systems, building the infrastructure and methodologies that connect teleoperation, evaluation, and learning. This includes developing evaluation policies, defining task structures, and contributing to operator-facing interfaces that enable scalable and reliable data collection. The ideal candidate is highly experimental, systems-oriented, and comfortable working across software, robotics, and data pipelines, with a strong focus on turning ambiguous capability goals into measurable and actionable evaluation systems. Key job responsibilities - Design and implement evaluation frameworks to measure robot capabilities across structured tasks, edge cases, and real-world scenarios - Develop task definitions, success criteria, and benchmarking methodologies that enable consistent and reproducible evaluation of policies - Create and refine data collection protocols that generate high-quality, task-relevant datasets aligned with model development needs - Build and iterate on teleoperation workflows and operator interfaces to support efficient, reliable, and scalable data collection - Analyze evaluation results and collected data to identify performance gaps, failure modes, and opportunities for targeted data collection - Collaborate with engineering teams to integrate evaluation tooling, logging systems, and data pipelines into the broader robotics stack - Stay current with advances in robotics, evaluation methodologies, and human-in-the-loop learning to continuously improve internal approaches - Lead technical projects from conception through production deployment - Mentor junior scientists and engineers
IN, KA, Bangalore
Are you passionate about solving complex logistics challenges? Our Analytics team is at the forefront of enhancing delivery experiences through data-driven solutions and innovative technology. As a Research Scientist, you will join a team dedicated to optimizing our delivery network, ensuring reliable and efficient service to our customers. We are seeking an enthusiastic, customer-centric professional with strong analytical capabilities to drive impactful projects, implement advanced solutions, and develop scalable processes. In this role, you will have immediate ownership of business-critical challenges and the opportunity to make strategic, data-driven decisions that shape the future of our delivery operations. Your work will directly influence customer experience and operational excellence. The ideal candidate will possess both research science capabilities and program management skills, thriving in an environment that requires independent decision-making and comfort with ambiguity. This role offers the opportunity to make a significant impact on our advanced logistics network while working with pioneering technology and data science applications. Basic qualifications • 3+ years of building machine learning models for business application experience • Knowledge of programming languages such as C/C++, Python, Java or Perl • Experience programming in Java, C++, Python or related language • Experience with neural deep learning methods and machine learning Preferred qualifications: • PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field • 3+ years of extensive relevant research experience • Deep expertise in Machine Learning • Proficiency in programming • Core competency in mathematics and statistics • Track record of successful projects in algorithm design and product development • Publications at peer-reviewed conferences or journals • Strategic thinker with good execution skills • Exhibits excellent business judgment • Effective verbal and written communication skills • Experience working with real-world data sets and building scalable models from big data • Experience with modern modeling tools and frameworks such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow • Experience with large scale distributed systems
US, WA, Seattle
Build AI systems that help Amazon make better sustainability decisions at global scale. Our research questions require more than applying an existing model: they require new scientific methods, trustworthy data foundations, and a path from research hypothesis to production deployment. Sustainability Science and Innovation (SSI) is Amazon's applied research hub for environmental impact. We bring together applied scientists, environmental scientists, economists, and engineers to develop and scale solutions across carbon, water, waste, climate risk, and responsible supply chains—from early hypothesis to production deployment at Amazon scale. SSI is seeking a Senior Applied Scientist to own a research agenda at the intersection of artificial intelligence, data, and sustainability. The role will define the science roadmap, formulate and test hypotheses, establish evaluation standards, and lead solutions from early experimentation through production deployment. Working closely with economists, environmental scientists, engineers, and product leaders, the Senior Applied Scientist will determine which scientific and technical approaches can produce decision-ready results at Amazon scale. The work may include large language models, multimodal models, retrieval-augmented generation, foundation-model adaptation, and other modern machine-learning methods, selected according to the scientific problem rather than applied as ends in themselves. The role will also define how strategic models and datasets are discovered, evaluated, ingested, harmonized, governed, and maintained, because trustworthy AI depends on traceable evidence, stable data contracts, and reproducible evaluation. Applications may include product-level carbon estimation, climate-risk monitoring, and responsible-supply-chain assessment. This role is distinctive because Amazon’s operational scale creates scientific problems that few organizations can study, with unique access to global-scale sustainability data. You'll leverage this unique access to establish scientific methods, governance models, and evaluation standards that can scale across multiple programs. This role shapes not just what problems we solve, but how we solve them rigorously setting a template for AI-driven sustainability science across Amazon's global operations. Candidates do not need prior expertise in sustainability or climate science. The role requires a hands-on scientific leader who can develop rigorous AI and machine-learning methods, work effectively across disciplines, and translate uncertain research questions into measurable, production-ready solutions. Key job responsibilities • Own the research agenda and multi-year science roadmap for AI-enabled sustainability solutions. • Develop and evaluate modern AI and machine-learning methods, including foundation models, multimodal models, retrieval-augmented generation, and model adaptation. • Establish ex ante evaluation criteria, benchmarks, and launch thresholds that distinguish promising prototypes from production-ready methods. • Lead the full scientific lifecycle, from problem formulation and experimentation through production deployment and post-launch measurement. • Define the architecture and governance required to make strategic models and datasets discoverable, traceable, reproducible, and reusable. • Influence senior science, engineering, product, and sustainability stakeholders across organizational boundaries. • Mentor scientists and raise the scientific standard through technical reviews, publications, and reusable methods. About the team Diverse Experiences: World Wide Sustainability 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. Inclusive Team Culture: 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 (inclusive 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 flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve.
CN, 11, Beijing
北京职位 - 如果希望在北京工作,请投递本职位。 毕业时间:2026年10月 - 2027年9月之间毕业的应届毕业生 · 投递须知: 1 填写简历申请时,请把必填和非必填项都填写完整。提交简历之后就无法修改了哦! 2 学校的英文全称请准确填写。中英文对应表,请点击链接查看 https://docs.qq.com/sheet/DVmdaa1BCV0RBbnlR?tab=BB08J2 3 简历不限中英文。 如果您正在攻读计算机,AI,ML等相关专业的博士或硕士研究生,而且对应用科学家的工作感兴趣。如果您也喜爱深入研究棘手的技术问题并提出解决方案,用成功的产品显著地改善人们的生活。 那么,我们诚挚邀请您加入亚马逊的International Technology搜索团队改善Amazon的产品和服务。我们的目标是帮助亚马逊的客户找到他们所需的产品,并发现他们感兴趣的新产品。这会是一份收获满满的工作。您每天的工作都与全球数百万亚马逊客户的体验紧密相关。您将提出创新,基于TB级别的产品和流量数据设计模型。您将集成这些模型为客户提供服务,通过数据,建模和客户反馈来完成闭环。您对模型的选择需要能够平衡业务指标和响应时间的需求。 Key job responsibilities 基本要求 正在攻读计算机工程,计算机科学,AI,机器学习,运筹学,统计或相关领域的硕士或博士学位。 有AI,ML实验设计和统计分析的经验。 有使用代码和工具实现算法的经验。 至少能熟练地使用一种编程语言(例如Python,Java,C ++等)编码和解决问题。 加分项: 在顶级会议或者期刊上有论文发表。 技术视野好;能与技术团队成员深入讨论概念和算法,并对应用问题提出恰当的解决方案。 出色的批判性思维能力;能以口头和书面形式清楚地向团队沟通您的技术方案。