Incremental few-shot meta-learning via indirect discriminant alignment

We propose a method to train a model so it can learn new classification tasks while improving with each task solved. This amounts to combining meta-learning with incremental learning. Different tasks can have disjoint classes, so one cannot directly align different classifiers as done in model distillation. On the other hand, simply aligning features shared by all classes does not allow the base model sufficient flexibility to evolve to solve new tasks. We therefore indirectly align features relative to a minimal set of “anchor classes.” Such indirect discriminant alignment (IDA) adapts a new model to old classes without the need to re-process old data, while leaving maximum flexibility for the model to adapt to new tasks. This process enables incrementally improving the model by processing multiple learning episodes, each representing a different learning task, even with few training examples. Experiments on few-shot learning benchmarks show that this incremental approach performs favorably compared to training the model with the entire dataset at once.
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US, CA, Irvine
Job summaryAs the Applied Science Manager within Personalization, you will help build a team that leads creation and innovation on the next generation of Recommendation and Personalization technologies on Amazon. Our team owns creating recommendation solutions that understand long-term customer shopping patterns, Spanning Academia, research, and applied machine learning techniques operating at world-class scale, we focus on recommending the right product to the right customer at the right time. You will be surrounded by thought-leaders in the Personalization space who are patent-leaders within Amazon.In Personalization we use state-of-the-art machine learning techniques and A/B testing to run experiments on some of Amazon’s most prominent and valuable pages. We work on a diverse range of products, building real-time, low-latency recommendation and ranking systems as well as building algorithms for understanding customer behavior and generating recommendations content. You will hone your skills in areas such as deep learning and collaborative filtering while building scalable industrial machine learning systems that handle millions of requests a day. You will lead a collaborative team of experienced engineers. You will have a unique opportunity to drive direct, measurable impact to our customers, powering features on Amazon.About the team: Our team has the autonomy to decide where we can have the most impact and get down to experimenting. We love metrics and the fast pace. We analyze data to uncover potential opportunities, generate hypotheses, and test them. We refuse to accept constraints, internal or external, and have a strong bias for action. We imagine, build prototypes, validate ideas, and launch follow-up experiments from the successful ones.About you: You are an entrepreneurial Applied Science Manager with an interest in machine learning, data science, search, or recommendation systems. You love keeping abreast of the latest technology and use it to help you innovate. You have strong leadership qualities, great judgment, clear communication skills, and a track record of delivering great products and hiring/coaching successful teams. You enjoy working hard, having fun, and making history!
IN, KA, Bangalore
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US, CA, Sunnyvale
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US, WA, Seattle
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US, WA, Redmond
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GB, Cambridge
Job summaryWe are looking for someone who is excited to apply cutting-edge techniques from deep learning, speech or natural language processing (NLP) to the text-to-speech (TTS) technology behind Alexa and our AWS cloud speech service.As a Machine Learning Scientist you will be responsible for leading the development and launch of core product features. You will have significant influence on our overall strategy by helping define new product features and carry out research to demonstrate their impact.You will have the opportunity to solve hard problems with voice – we’ve spent years of invention on this. When we started working on this, the technology didn’t even exist – we had to invent it. Join us if you want to apply your deep learning skills in a dynamic field that is revolutionising the way people interact with devices and services.We believe that voice will fundamentally improve the way people interact with technology. It can make the complex simple—it’s the most natural and convenient user interface. Voice is going to be a big part of our future and we are inventing it here.Key job responsibilities· Use your expertise in deep learning to research and implement novel approaches to make improvements to our text-to-speech technology.· Publish your work at scientific conferences,· Lead and mentor junior engineers and scientists.· Participate in the design, development, evaluation, deployment and updating of data-driven models and analytical solutions for spoken language applications.
US, WA, Bellevue
Job summaryAt Amazon we strive to be the most innovative and customer centric company on the planet. Come work with us while we are developing our Science and Technology to deliver the best solutions for our vendors, warehouses and carriers. Help us solve complex problems impacting billions of dollars per year while partnering with world class scientists and researchers. Our mission is to build the most efficient and customer-obsessed solution on the planet. We aim to leverage cutting edge technologies in and techniques, and operate high volume, high efficiency, low latency, and high availability services.You’ll design, model, develop and implement state of the art models and solutions used by Amazon worldwide and will regularly interact with engineering and business leadership. You will participate in the planning and execution of technology projects and operational excellence initiatives. The focus of this role is to research, develop, and deploy models that will inform and support our business. You will have the opportunity to work with some of the leading scientists in the areas of vehicle routing, meta-heuristics, and market analysis, , and methodologies.Tasks/ Responsibilities:· Contribute to the mid- and long-term strategic planning studies and analysis.· Lead and partner with the engineering and operations to drive modeling and design for complex business problems.· Develop accurate and scalable mathematical programming, heuristic, and models to solve our hardest problems.· Lead complex modeling analyses to aid management in making key business decisions and set new policies.Amazon is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation / Age.
US, WA, Seattle
Job summaryAre you excited about influencing the payment experience of millions of customers worldwide ? The moment a customer makes a payment on Amazon is when trust is established – trust that the item is delivered on time, a refund is provided quickly if needed, a digital movie purchased will play immediately, a seller receives their disbursement, and hundreds of other experiences across Amazon when a customer completes a payment. The Payment Acceptance & Experience (PAE) team, within the Consumer Payments organization, has the mission to build the most trusted, intuitive, and accessible payment experience on Earth. Applied Science & Machine Learning Engineering (PAE ASMLE) is the core machine learning team within PAE. The team has a mission to enhance customer payments experience that requires advancing the state of the art in machine learning. We work backwards from the customer to create value for them by leveraging an underlying applied science methodology. We deploy our solutions through Native AWS services that operate at Amazon scale. We strive to publish our solutions and share our findings so that the broader Amazon scientific community can benefit.As an applied scientist on our team, your role is to leverage your strong background in Computer Science and Machine Learning to help build the next generation of our model development and assessment pipeline, harness and explain rich data at Amazon scale, and provide automated insights to improve machine learned solution that impacts Payments experience of millions of customers every day. This role requires a pragmatic technical leader comfortable with ambiguity, capable of summarizing complex data and models through clear visual and written explanations. The ideal candidate will have experience with machine learning models and applying science to various business contexts. We are particularly interested in experience applying predictive modeling, natural language processing, deep learning, and reinforcement learning at scale. Additionally, we are seeking candidates with strong rigor in applied sciences and engineering, creativity, curiosity, and great judgment.Your responsibilities include:. Analyze the data and metrics resulting from traffic into Amazon Consumer Payments experiences.. Design, build, and deploy effective and innovative ML solutions to improve various components of the Consumer Payments experience, using predictive modeling, recommendations, anomaly detection, ranking, and forecasting.. Evaluate the proposed solutions via offline benchmark tests as well as online A/B tests in production.. Publish and present your work at internal and external scientific venues in the fields of ML/NLP/IR/Forecasting.Your benefits include:. Working on a high-impact, high-visibility product, with your work improving the experience of millions of customers.. The opportunity to use (and innovate) state-of-the-art ML methods to solve real-world problems.. Excellent opportunities, and ample support, for career growth, development, and mentorship.. Competitive compensation, including relocation support.The PAE ML team operates primarily out of Amazon's Seattle office. We are a new and expanding team where you will have an opportunity to influence our goals and mission. We collaborate with Software Engineering, Data Engineering, Product Management and Marketing teams within Amazon Consumer Payments to solve and deploy machine learning solutions at scale.Please visit for more information
GB, Cambridge
Job summaryJob summaryWe research and develop question understanding techniques, deployed to Alexa world-wide.Key job responsibilitiesWe have an exciting position for a NLP/ML scientist to join Alexa AI. Our team makes Alexa smarter by delivering an end-to-end natural language question answering (QA) technology. We build advanced QA models based on constructing a high precision large scale knowledge graph from multiple sources (e.g. facts extraction from text at Internet-scale; linking and aligning open and proprietary knowledge-bases); developing natural language understanding models; and generating natural language responses based on query results on our knowledge graph.To achieve our ambition we need to develop methods that lie beyond the cutting edge academic and industrial research of today and as a scientist, you will bring academic and/or industrial practical experience and create novel solutions to complex problems at massive scale. We are particularly interested in problems of fact extraction, entity linking, natural language understanding, semantic parsing, natural language generation, masked language models, cross-lingual NLP models, and weakly supervised methods of learning (self-supervised, transfer learning, semi-supervised, curriculum learning).As a research led team, we have been publishing and contributing to the scientific community and you can find some of our recent work at: Rongali et al, "Don't Parse, Generate! A Sequence to Sequence Architecture for Task-Oriented Semantic Parsing",; Harkous et al, "Have Your Text and Use It Too! End-to-End Neural Data-to-Text Generation with Semantic Fidelity",; Sen et al, "What do Models Learn from Question Answering Datasets?",; Thorne et al, FEVER: a large-scale dataset for fact extraction and verification, day in the lifeResearch and development of models for question answering, fact extraction, and reasoning. Publish your findings and innovations in papers.About the teamWe research and develop end-to-end question answering techniques, deployed to Alexa world-wide.
US, WA, Seattle
Fashion is extremely fast-moving, visual, subjective, and it presents numerous challenges in areas such as search relevance ranking and optimization, product discovery experience including recommendations and personalization. The vision for Amazon Fashion is to make Amazon the number one online shopping destination for Fashion customers by providing large selections, inspiring and accurate recommendations and customer experience. Are you excited by solving Fashion customer and business problems by applying machine learning and big data technologies? Are you passionate about building systems that process massive amounts of data and make real customer and business impact?The main focus of Softlines Discovery Science team is to innovate and build engaging search and browse experience for Amazon Fashion customers including organic search relevance ranking, content recommendation and optimization, and understanding of fashion customers shopping intent. The team is looking for an Applied Scientist who is proficient in Machine Learning and can apply the concepts to solve large-scale customer facing problem. We closely collaborate with the core Amazon Search community on building better search algorithms with profound customer impact. The team integrates knowledge on causal Inference, and Econometric/Economic Methodologies to derive actionable insights that change the search results towards improving the long term engagement of our customers. We also develop Statistical Models and Algorithms to drive strategic business decisions and improve operations. Additionally, we are building deep learning models and system to best utilize Amazon customer and product information, such as customer review, product images, etc, for more personalized Softlines shopping experience. We are an interdisciplinary team of Engineers, and Scientists incubating and building day one solutions using cutting-edge technology, to solve large scale problems at Amazon. This role will challenge you to utilize cutting-edge machine learning techniques in the domain of search ranking, deep recommendation system, and computer vision to deliver significant impact for the business.Major Responsibilities:· Act as the key contributor in Machine Learning and drive full life-cycle Machine Learning projects.· Participate in technical efforts within this team and collaboration with other science 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 tests.· Establish scalable, efficient, automated processes for large-scale data mining, machine-learning model development, model validation and serving.· Work closely with software engineers and product managers to assist in productionizing your ML models.· Explore new research initiatives to help shape our long-term science vision.
US, WA, Seattle
Job summaryThe Central AWS Econ team is dedicated to bringing the most trustworthy evidence-based analysis to the most strategic decisions for AWS leadership.Our studies impact strategic investments, service business model, resource allocation, product priorities and pricing models, go-to-market motions and more.This economist role partners with AWS business leaders across the organization to define and deliver on economic questions that guide their most strategic decisions. The successful candidate will be a problem solver who enjoys diving into data, is excited by difficult modeling challenges and ambiguous starting points, and possesses strong communication skills to effectively interface and collaborate with product, finance, planning and business teams.Specific questions include developing supporting economics for new business model, evaluating the relationship between short and long term growth, mapping and affecting the customer journey through different AWS products and cloud technologies.The Central AWS Econ team is dedicated to answering these (and many more) questions using quantitative, economic and statistical methods.Key Responsibilities:· Frame and conduct economic studies, from question definition to and communicating practical implications to senior leadership· Develop new repeatable data analysis pipelines to be used by non-economists
US, CA, San Francisco
Job summaryConversational interfaces are maturing and proliferating, but significant advances in conversational AI and related technologies will need to be made before a fully conversational web is possible. is seeking a creative, entrepreneurial, and customer-obsessed Applied Scientist who can apply cutting edge research and state-of-the-art machine learning algorithms as part of a new project that will push the boundaries of conversational AI. This position will require you to investigate and solve complex technical problems, innovate on behalf of customers, invent new technologies, and build cornerstone services to power the next generation of online conversational applications.The ideal candidate has a broad and deep background in machine learning, is passionate about science, is highly driven to learn and deploy new technologies, thrives in a fast-paced environment that requires the development of solutions to ambiguous and challenging problems, and enjoys collaborating with both technical and nontechnical peers. As part of our AI team, you will work as a hands-on practitioner and technical leader in multiple areas such as statistical modeling, NLP and NLU, and deep learning. You will formulate and test hypotheses, evaluate and implement ML techniques, train and test new models, and deliver new production services that will be used by customers around the world.Key job responsibilities· Develop novel modeling techniques for pattern recognition, prediction, classification, and other complex data science problems· Develop prototypes and collaborate with stakeholders to assess the feasibility of selected approaches· Write high quality code and contribute to our codebase of scientific applications using relevant technologies· Contribute to strategic planning and project management for a variety of technical initiatives· Effectively communicate with customers, senior management, and colleagues with diverse roles and technical backgrounds· Document methodologies and increase our institutional knowledge based on experimental results and operationalized solutionsAbout the is a wholly owned subsidiary of At, we solve ML problems in natural language processing and understanding, search relevance and ranking, and digital behavior measurement and prediction. We have been gathering and analyzing data from online sources for more than 20 years, with terabytes of archived web content, a data-contributing panel of millions of users in countries around the world, and decades of experience as a leading provider of competitive analytics and marketing intelligence services. For more information, visit
Job summary“Amazon Science gives you insight into the company’s approach to customer-obsessed scientific innovation. Amazon fundamentally believes that scientific innovation is essential to being the most customer-centric company in the world. It’s the company’s ability to have an impact at scale that allows us to attract some of the brightest minds in artificial intelligence and related fields. Our scientists continue to publish, teach, and engage with the academic community, in addition to utilizing our working backwards method to enrich the way we live and work.”Please visit for more informationAmazon Exports and Expansion builds new experiences which help our customers across the world access the benefits of shopping on Amazon to find products sourced locally for them or exported from other Amazon marketplaces. Do you want to improve how shoppers around the world discover and purchase products that delight them?We are looking for an Applied Scientist who can apply the latest research, state of the art algorithms and machine learning to build highly scalable systems in the international e-Commerce space. Right candidate will develop algorithms and models to handle unique cross border shopping problems such as improving selection data quality, improved product discovery or offering scalable, highly localized customer experience to name few.Does the challenge of AI solving some of the pain points of millions of international shoppers from 100+ countries, in multiple currencies and excite you? Have you ever wanted to work on machine learning problems that will make a lasting impact, solving key problems that impact the experience of millions of Amazon customers? If you are passionate about solving complex problems, in a challenging environment, we would love to talk with you.As a member of our team you will develop and evaluate machine learning models using large data-sets, cloud services, customer behavior, transactional history to improve our customer’s experience. Working closely with best-in-class engineers you will have the opportunity to apply a variety of machine learning algorithms, including deep learning, and work on one of the world's largest data sets to influence the long term evolution of our technology roadmap. You will need to be entrepreneurial, able to deal with ambiguity and work in a highly collaborative environment.
IN, KA, Bengaluru
The Alexa Automatic Speech Recognition (ASR) science team in India is rapidly growing. The team is responsible for advancing Alexa’s core ASR technology (in collaboration with the EU and US counterparts) and building highly accurate ASR production models in multiple languages, such as English dialects (UK, AU, NZ, IN) and Indic (Hindi etc.) languages.The challenge is ASR models must generalize to various device form factors (smart speaker, multi-media devices, etc.), acoustic conditions (far-field, close-talk, mobile, and noisy), and content (natural conversations etc.). As part of the expansion, the team will be responsible for complex ML technologies such as (i) learning without relying on human transcribed data by leveraging abundant unlabelled data via semi-supervised learning (SSL) and self-supervised learning, and customer feedback signals through weak-supervision (WS) (ii) Online Learning and Lifelong Learning, which requires a major overhaul of the learning infrastructure and ML algorithms as data will not be stored for training (iii) Privacy-preserving Federated-Learning, which enables training where audio does not even leave the devices. (iv) multilingual ASR technology, where a single ASR model will serve multiple languages (e.g., Indic languages). Apart from working on cutting-edge ML technology, you will have the opportunity to work on some exciting still confidential new products and also publish your work in top-tier conferences.We are looking to hire Applied Scientists, Senior Applied Scientists and Applied Science Managers, at all levels. For Applied Science roles, Masters or PhD with solid understanding of Machine Learning (ML), Algorithms and Coding is a minimum requirement. Prior experience in ML projects and publications in top-tier conferences are preferred. If you are interested, please apply below.
CA, ON, Toronto
Job summaryThe Sponsored Display Advertising team has an opening for an outstanding ML scientist who is passionate about applying advanced ML and statistical techniques to solve real-world challenges. Amazon's Sponsored Display Advertising program serves millions of personalized Ads every day. We buy Ad impressions in real-time auctions and algorithmically deliver the most relevant Ad. We delight in data, and are constantly working to enhance and improve our models. We relentlessly optimize to keep delivering the best possible Ads for our customers.You will work in an agile and fast-paced team of scientists and software engineers. The team is building a number of new advertising products, including dynamic video advertising, to improve the range of offerings for our advertisers and provide new Ad experiences for our customers. As a scientist on the team, you can be involved in every aspect of the process - from idea generation, business analysis and scientific research, through to development and deployment of advanced models - giving you a real sense of ownership. The systems that you help to build will operate at massive scale to display ads to customers around the world. From day one, you will be working with experienced scientists, engineers, and designers who love what they do.We are looking for ML scientists who can delight our customers by continually learning and inventing. Our ideal candidate is an experienced ML scientist who has a track-record of performing analysis and applying statistical techniques to solve real business problems, who has great leadership and communication skills, and who is motivated to achieve results in a fast-paced environment. The position offers an exceptional opportunity to grow your technical and non-technical skills and make a real difference to the Amazon Advertising business.Key responsibilities:· Rapidly design, prototype and test many possible hypotheses in a high-ambiguity environment, making use of both quantitative analysis and business judgment.· Collaborate with software engineering teams to integrate successful experimental results into large-scale, highly complex Amazon production systems.· Report results in a manner which is both statistically rigorous and compellingly relevant, exemplifying good scientific practice in a business environment.· Promote the culture of experimentation and applied science at Amazon.
JP, 13, Meguro
Job summary*Please submit English resume when you apply for the job.Sellers are our customers. Our mission is to help every seller grow and succeed on Amazon. Our team invents, test and launches some of the most innovative services, technology and processes for our sellers.Amazon is looking for a talented and passionate hands-on Data Scientist to build world class statistical and machine learning models to understand our sellers, and deliver the right recommendation to help them grow.They’ll be comfortable with ambiguity and enjoy working in a fast-paced, diverse and dynamic environment. The position also requires collaboration with other scientists, engineers, Product and Marketing ManagersThe Data Scientist is accountable for:(1) Deeply understanding the most challenging business questions and use data / modelling / analysis to articulate possible root cause analysis and solutions.(2) Managing and executing entire projects or components of large projects from start to finish including project management, data gathering and manipulation, synthesis and modeling, problem solving, and communication of insights and recommendations.(3) Developing and scaling end-to-end ML Models and solutions(4) Partnering with Other Data scientists and Economists to design and run experiments, research new algorithms, and prove incrementality and drive growth.(5) Understanding drivers, impacts, and key influences on seller growth dynamics.(6) Automating feedback loops for algorithms in production.(7) Utilizing Amazon systems and tools to effectively work with terabytes of data.[Work Life Harmony]We believe, it is important to spend private time such as spending time with your family or doing anything you like to spur innovation. Amazon promotes a fulfilling and flexible work style according to the work volume and lifestyle of each employee. (Example: Flex Time, Work from Home, Maternity /Parenting /Family Care Leave etc.)
US, WA, Seattle
Job summaryThe Sourcing Guidance team is looking for an Applied Scientist to join our team in building science solutions at scale. Our team applies Machine Learning, Reinforcement Learning, Causal Inference, and Econometrics/Economics to derive actionable insights about the complex economy of Amazon’s retail business. We also develop Statistical Models and Algorithms to drive strategic business decisions and improve operations. We are an interdisciplinary team of Economists, Engineers, and Scientists incubating and building day one solutions using cutting-edge technology, to solve some of the toughest business problems at Amazon.You will work with business leaders, scientists, and economists to translate business and functional requirements into concrete deliverables, including the design, development, testing, and deployment of highly scalable ML models. You will partner with scientists, economists, and engineers to help invent and implement scalable ML, RL, and econometric models while building tools to help our customers gain and apply insights. This is a unique, high visibility opportunity for someone who wants to have business impact, dive deep into large-scale economic problems, enable measurable actions on the Consumer economy, and work closely with scientists and economists. We are particularly interested in candidates with experience building predictive models and working with distributed systems.As an Applied Scientist, you bring business and industry context to science and technology decisions. You set the standard for scientific excellence and make decisions that affect the way we build and integrate algorithms. Your solutions are exemplary in terms of algorithm design, clarity, model structure, efficiency, and extensibility. You tackle intrinsically hard problems, acquiring expertise as needed. You decompose complex problems into straightforward solutions.To know more about Amazon science, Please visit
US, CA, San Diego
Job summaryThe Sourcing Guidance team is looking for an Applied Scientist to join our team in building science solutions at scale. Our team applies Machine Learning, Reinforcement Learning, Causal Inference, and Econometrics/Economics to derive actionable insights about the complex economy of Amazon’s retail business. We also develop Statistical Models and Algorithms to drive strategic business decisions and improve operations. We are an interdisciplinary team of Economists, Engineers, and Scientists incubating and building day one solutions using cutting-edge technology, to solve some of the toughest business problems at Amazon.You will work with business leaders, scientists, and economists to translate business and functional requirements into concrete deliverables, including the design, development, testing, and deployment of highly scalable ML models. You will partner with scientists, economists, and engineers to help invent and implement scalable ML, RL, and econometric models while building tools to help our customers gain and apply insights. This is a unique, high visibility opportunity for someone who wants to have business impact, dive deep into large-scale economic problems, enable measurable actions on the Consumer economy, and work closely with scientists and economists. We are particularly interested in candidates with experience building predictive models and working with distributed systems.As an Applied Scientist, you bring business and industry context to science and technology decisions. You set the standard for scientific excellence and make decisions that affect the way we build and integrate algorithms. Your solutions are exemplary in terms of algorithm design, clarity, model structure, efficiency, and extensibility. You tackle intrinsically hard problems, acquiring expertise as needed. You decompose complex problems into straightforward solutions.To know more about Amazon science, Please visit
Job summaryPayments Security team is looking for an Applied Scientist to apply formal verification, program analysis, and constraint-solving to prove the correctness of critical systems. In this role, you will work closely with internal security teams to design and build formal verification systems that continuously assess safety and security. You will build on top of existing formal verification tools developed by AWS and develop new methods to apply those tools at scale. You will need to be innovative, entrepreneurial, and adaptable. We like to move fast, experiment, iterate and then scale quickly, thoughtfully balancing speed and quality.
US, WA, Seattle
Job summaryWe are a team of doers working passionately to apply cutting-edge advances in technology to solve real-world problems. As a Research Scientist, you will work with a unique and gifted team developing exciting products for consumers and collaborate with cross-functional teams. Our team rewards intellectual curiosity while maintaining a laser-focus in bringing products to market. Competitive candidates are responsive, flexible, and able to succeed within an open, collaborative, entrepreneurial, startup-like environment. At the cutting edge of both academic and applied research in this product area, you have the opportunity to work together with some of the most talented scientists, engineers, and product managers.Here at Amazon, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon’s culture of inclusion is reinforced within our 14 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.Work/life BalanceOur team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.Mentorship & Career GrowthOur team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future.