Amazon Recruitment 2020 Off Campus Drive Hiring Freshers of Any Degree Graduates
Amazon Recruitment 2020: Amazon.com strives to be Earth’s most customer-centric company where people can find and discover virtually anything they want to buy online. By giving customers more of what they want – low prices, vast selection, and convenience – Amazon.com continues to grow and evolve as a world-class e-commerce platform. Amazon’s evolution from a Web site to e-commerce partner to development platform is driven by the spirit of innovation that is part of the company’s DNA. The world’s brightest technology minds come to Amazon.com to research and develop technology that improves the lives of shoppers and sellers around the world.
Company Name: Amazon
Company Website: Amazon
Wikipedia: Amazon Wiki
Position: Software Development Engineer
Job Location: Hyderabad
Experience Level: 0 – 2 Years
Degree Needed: B.E/B.Tech/B.Sc
Passout Batch: 2018/2019/2020
Package: As Per IT Standards
Latest Upcoming off Campus Drive: Apply ASAP
Eligibility of Amazon Recruitment 2020:
- BS in Major Stream, or equivalent background in data structures, algorithms, object-oriented design and systems architecture.
- 0-2+ years professional experience building and operating scalable distributed systems across the full software lifecycle including design, implementation, testing, operations, and maintenance.
- Fluency in one or more modern programming languages such as Java, C# or C++.
- Experience across front-end user interfaces, business logic, and data tiers. · Experience serving as technical lead, including mentorship of more junior software developers.
- Good problem solving skills
- Good understanding of CS
- some experience or strong interest in the following topics:
- designing internet-scale public APIs.
- building solutions for enterprises, context-awareness, pervasive computing, and/or application of machine learning
- working with modern tools for big data storage and analysis (e.g., AWS, Apache Spark, Hadoop, SQL, NoSQL
- Foundational machine learning models and concepts: regression, random forest, boosting, GBM, NNs, HMMs, CRFs, MRFs, deep learning.
Apply Link: Click here
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