Join to apply for the Machine Learning Engineer II, Just Walk Out (JWO) role at Amazon Web Services (AWS)
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Join to apply for the Machine Learning Engineer II, Just Walk Out (JWO) role at Amazon Web Services (AWS)
Description
As part of the AWS Solutions organization, we have a vision to provide business applications, leveraging Amazons unique experience and expertise, that are used by millions of companies worldwide to manage day-to-day operations. We will accomplish this by accelerating our customers businesses through delivery of intuitive and differentiated technology solutions that solve enduring business challenges. We blend vision with curiosity and Amazons real-world experience to build opinionated, turnkey solutions. Where customers prefer to buy over build, we become their trusted partner with solutions that are no-brainers to buy and easy to use.Description
As part of the AWS Solutions organization, we have a vision to provide business applications, leveraging Amazons unique experience and expertise, that are used by millions of companies worldwide to manage day-to-day operations. We will accomplish this by accelerating our customers businesses through delivery of intuitive and differentiated technology solutions that solve enduring business challenges. We blend vision with curiosity and Amazons real-world experience to build opinionated, turnkey solutions. Where customers prefer to buy over build, we become their trusted partner with solutions that are no-brainers to buy and easy to use. Amazon Go is a new kind of store with no lines and no checkoutyou just grab and go! Customers simply use the Amazon Go app to enter the store, take what they want from our selection of fresh, delicious meals and grocery essentials, and go! We are looking for a talented Machine Learning Engineer to join our team. In this role, you will be responsible for translating business and functional requirements into concrete deliverables with the design, development, testing, and deployment of highly scalable distributed services. You will partner with scientists and other engineers to help investigate, evaluate, implement, and connect sophisticated algorithms to our cloud based engines. You will design, build, evaluate prototypes and production-ready components. Candidates should also be very agile in developing flexible software with respect to scientific, experimentation methods and usage patterns. You will have the opportunity to work with scalable model development tools using SageMaker, AWS, Nvidia GPUs and Docker. You will learn techniques for automating model training, evaluation, deployment and monitoring using machine learning pipelines. You will work closely with researchers in building algorithms ranging from classical machine learning to foundational multi-modal models on diverse types of signals. Our checkout-free shopping experience is made possible by our Just Walk Out Technology, which automatically detects when products are taken from or returned to the shelves and keeps track of them in a cart. When youre done shopping, you can just leave the store. Shortly after, well charge your Amazon account and send you a receipt. Check it out at amazon.com/go. Designed and custom-built by Amazonians, our Just Walk Out Technology uses a variety of technologies including computer vision, sensor fusion, and advanced machine learning. Innovation is part of our DNA! Our goal is to be Earths most customer centric company and we are just getting started. We need people who want to join an ambitious program that continues to push the state of the art in computer vision, machine learning, distributed systems and hardware design. Key job responsibilities In this role, you will be responsible for translating business and functional requirements into concrete deliverables with the design, development, testing, and deployment of highly scalable distributed services. You will partner with scientists and other engineers to help investigate, evaluate, implement, and connect sophisticated algorithms to our cloud based engines. You will design, build, evaluate prototypes and production-ready components. Candidates should also be very agile in developing flexible software with respect to scientific, experimentation methods and usage patterns. A day in the life Inclusive Team Culture 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. Amazons 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 Balance Our team puts a high value on work-life balance. It isnt about how many hours you spend at home or at work; its 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 Growth Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and were building an environment that celebrates knowledge sharing and mentorship. We care about your career growth and strive to assign opportunities based on what will help each team member develop into a better-rounded contributor. Basic QualificationsReferrals increase your chances of interviewing at Amazon Web Services (AWS) by 2x
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