Amazon Web Services (AWS) · Mountain View, CA
Skills: AWS
Description AWS Applied AI Solutions (AAIS) is building toward a future where every business innovates with Amazon AI teammates. To get there, we build AI solutions that improve human capabilities and transform entire business functions. We create end-to-end products that surprise and delight out-of-the-box, making complex things easy and hard things possible, with no cloud experience required. We start with customers who embrace the future and build bridges to meet the rest where they are. We pursue ambitious opportunities with conviction, and we are looking for builders who share that mindset.
Amazon Personalize is a deep learning AWS Service that makes it easy for developers to create individualized recommendations for customers. We're building a large-scale machine learning platform and are looking for senior engineers to architect and develop the platform.
If you have prior experience in building and scaling large-scale systems and ML pipelines and enjoy extracting maximum performance at every layer of the stack, we should talk.
You'll collaborate with product managers, scientists, and other engineers to rapidly deliver production ready solutions that have a broad business impact. This is a unique opportunity to join a fast-growing startup within AWS AI where you'll be working on latest technology, influence, and shape the technology, product, and business.
Key job responsibilities
Collaborate with experienced cross-disciplinary Amazonians to conceive, design, and bring innovative products and services to market. Design and build innovative technologies in a large distributed computing environment and help lead fundamental changes in the industry. Create solutions to run predictions on distributed systems with exposure to innovative technologies at incredible scale and speed. Build distributed storage, index, and query systems that are scalable, fault-tolerant, low-cost, and easy to manage and use. Design and code the right solutions starting with b …truncated… cate…
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