Algorithms, Artificial Intelligence (AI), Communication Skills, Computer Science, Computer Services, Computer Vision, Cross-Functional, Customer Relations, Customer Support/Service, Deep Learning, Detail Oriented, Leading Edge Technology, Machine Tool, Mentoring, Mobile Devices, Modeling Languages, Object Modeling, Problem Solving Skills, Product/Service Launch, Resolve Customer Issues, Robotics, Scripting (Scripting Languages), Team Player, Technology White Papers, Use Cases
Shape the Future of Visual Intelligence
Are you passionate about pushing the boundaries of computer vision and shaping the future of visual intelligence? Join Amazon and embark on an exciting journey where you"ll develop cutting-edge algorithms and models that power our groundbreaking computer vision services, including Amazon Rekognition, Amazon Go, Visual Search, and more!
At Amazon, we"re combining computer vision, mobile robots, advanced end-of-arm tooling, and high-degree of freedom movement to solve real-world problems at an unprecedented scale. As an intern, you"ll have the opportunity to build innovative solutions where visual input helps customers shop, anticipate technological advances, work with leading-edge technology, focus on highly targeted customer use-cases, and launch products that solve problems for Amazon customers worldwide.
Throughout your journey, you"ll have access to unparalleled resources, including state-of-the-art computing infrastructure, cutting-edge research papers, and mentorship from industry luminaries. This immersive experience will not only sharpen your technical skills but also cultivate your ability to think critically, communicate effectively, and thrive in a fast-paced, innovative environment where bold ideas are celebrated.
Join us at the forefront of applied science, where your contributions will shape the future of AI and propel humanity forward. Seize this extraordinary opportunity to learn, grow, and leave an indelible mark on the world of technology.
Amazon has positions available for Computer Vision Applied Science Internships in, but not limited to, Arlington, VA; Boston, MA; Cupertino, CA; Minneapolis, MN; New York, NY; Portland, OR; Santa Clara, CA; Seattle, WA; Bellevue, WA; Santa Clara, CA; Sunnyvale, CA.
Key job responsibilities
We are particularly interested in candidates with expertise in: Vision - Language Models, Object Recognition/Detection, Computer Vision, Large Language Models (LLMs), Programming/Scripting Languages, Facial Recognition, Image Retrieval, Deep Learning, Ranking, Video Understanding, Robotics
In this role, you will work alongside global experts to develop and implement novel, scalable algorithms and modeling techniques that advance the state-of-the-art in areas of visual intelligence. You will tackle challenging, groundbreaking research problems to help build solutions where visual input helps the customers shop, anticipate technological advances, work with leading edge technology, focus on highly targeted customer use-cases, and launch products that solve problems for Amazon customers.
The ideal candidate should possess the ability to work collaboratively with diverse groups and cross-functional teams to solve complex business problems. A successful candidate will be a self-starter, comfortable with ambiguity, with strong attention to detail and the ability to thrive in a fast-paced, ever-changing environment.
A day in the life
- Collaborate with Amazon scientists and cross-functional teams to develop and deploy cutting edge computer vision solutions into production.
- Dive into complex challenges, leveraging your expertise in areas such as Vision-Language Models, Object Recognition/Detection, Large Language Models (LLMs), Facial Recognition, Image Retrieval, Deep Learning, Ranking, Video Understanding, and Robotics.
- Contribute to technical white papers, create technical roadmaps, and drive production-level projects that will support Amazon Science.
- Embrace ambiguity, strong attention to detail, and a fast-paced, ever-changing environment as you own the design and development of end-to-end systems.
- Engage in knowledge-sharing, mentorship, and career-advancing resources to grow as a well-rounded professional.
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Amazon.com Inc
At Amazon, we don’t wait for the next big idea to present itself. We envision the shape of impossible things and then we boldly make them reality. So far, this mindset has helped us achieve some incredible things. Let’s build new systems, challenge the status quo, and design the world we want to live in. We believe the work you do here will be the best work of your life.
Wherever you are in your career exploration, Amazon likely has an opportunity for you. Our research scientists and engineers shape the future of natural language understanding with Alexa. Fulfillment center associates around the globe send customer orders from our warehouses to doorsteps. Product managers set feature requirements, strategy, and marketing messages for brand new customer experiences. And as we grow, we’ll add jobs that haven’t been invented yet.
It’s Always Day 1
At Amazon, it’s always “Day 1.” Now, what does this mean and why does it matter? It means that our approach remains the same as it was on Amazon’s very first day – to make smart, fast decisions, stay nimble, invent, and stay focused on delighting our customers. In our 2016 shareholder letter, Amazon CEO Jeff Bezos shared his thoughts on how to keep up a Day 1 company mindset. “Staying in Day 1 requires you to experiment patiently, accept failures, plant seeds, protect saplings, and double down when you see customer delight,” he wrote. “A customer-obsessed culture best creates the conditions where all of that can happen.” You can read the full letter
here
Our Leadership Principles
Our Leadership Principles help us keep a Day 1 mentality. They aren’t just a pretty inspirational wall hanging. Amazonians use them, every day, whether they’re discussing ideas for new projects, deciding on the best solution for a customer’s problem, or interviewing candidates. To read through our Leadership Principles from Customer Obsession to Bias for Action, visit
https://www.amazon.jobs/principles