Amazon Careers

Internship in Amazon | Applied Scientist Intern | Amazon Careers | Bangalore | Latest Internship 2021


Internship in Amazon | Applied Scientist Intern | Amazon Careers | Bangalore | Latest Internship 2021

About Company

Amazon is coordinated by four principles: customer obsession rather than competitor focus, energy for improvement, commitment to useful significance, and long stretch reasoning. We are driven by the enthusiasm of building headways, envisioning things, and offering sorts of help that change lives. We embrace better methodologies for finishing things, make decisions quickly, and are not reluctant to fail. We have the augmentation and limits of an enormous association, and the spirit and heart of somewhat one.

Job Description | Internship in Amazon

As an Applied Scientist, you will bring measurable displaying and AI headways to information examination for client confronting arrangements in complex mechanical settings. You will be working in a speedy, cross-disciplinary group of analysts who are pioneers in the field. You will take on testing issues, distil genuine necessities, and afterward convey arrangements that either influence existing scholarly and modern exploration, or use your own out-of-the-container commonsense reasoning. As well as thinking of novel arrangements and models, you might even have to convey these to creation in client confronting items.

Basic Qualifications | Internship in Amazon

• Currently enrolled in degree program (either MS or Ph.D.) in Electrical Engineering, Computer Science, Computer Engineering, Mathematics, or related field with specialization in machine learning, NLP, ASR, deep learning, computer vision or related fields.
• Strong working knowledge of programming languages such as C/C++, Java, or Python (SciPy, RPy2, etc).
• Practical machine learning experience

Internship in Amazon
Preferred Qualifications | Internship in Amazon

• Research experience related to machine learning, deep learning, NLP, computer vision
• Published and/or presented papers at ICASSP, ICML, NIPS, KDD, CVPR or similar top-tier conferences and events

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