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Amazon Applied Scientist Prime Video Sports Israel, Tel Aviv District 805309110
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Key job responsibilities
We are looking for an Applied Scientist with domain expertise in Computer Vision or Recommendation Systems to lead development of new algorithms and E2E solutions. You will be part of a team of applied scientists and software development engineers responsible for research, design, development and deployment of algorithms into production pipelines. As a technologist, you will also drive publications of original work in top-tier conferences in Computer Vision and Machine Learning. You will be expected to deal with ambiguity! We're looking for someone with outstanding analytical abilities and someone comfortable working with cross-functional teams and systems. You must be a self-starter and be able to learn on the go.
- Experience building machine learning models or developing algorithms for business application
- PhD, or a Master's degree and experience in CS, CE, ML or related field research
- Experience programming in Java, C++, Python or related language
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
PREFERRED QUALIFICATIONS
- Experience using Unix/Linux
- Experience in professional software development
- Experience in patents or publications at top-tier peer-reviewed conferences or journals
- Experience in building production grade deep learning models for computer vision, recommendation systems, or related fields.
- Experience with defining research and development practices in an applied environment
- Solid knowledge of big data and cloud technologies (e.g., Spark, AWS, etc.)
- Scientific thinking and the ability to invent, a track record of thought leadership and contributions that have advanced the field
- Track record in creating novel algorithms and advancing the state of the art ·
- Technical writing, verbal communication, and cross discipline collaboration skills
- Background in classical CV algorithms is a plus.
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