Applied Scientist - Amazon Video - X-Men Team (Seattle, WA)
Can we automatically figure out that a video is a futuristic sci-fi movie that is also a coming-of-age story with a strong female lead and themes of teamwork and revenge?
What age group will that kids TV show really appeal to? Will it also speak to their parents?
What are the relationships between the characters in the show and how do they change?
The answers to these questions and others like them are core to helping Amazon Video's business in many ways, including customer experience, recommendations, and others. The Metadata Enrichment Team is charged with creating rich, accurate descriptions of videos from a variety of sources. We're looking for an Applied Scientists (AS) with a background in Aritifical Intelligence (AI) and Machine Learning (ML), and interests in Natural Language Processing (NLP) and/or Computer Vision (CV) to work closely with a team of software development engineers to create solutions to these kinds of problems.
You will leverage heterogenous data sources and Amazon's large-scale computing resources to build models describing video content; and work with domain and ontology experts and engineers to help turn those models into production solutions. You will participate in the Amazon Video ML community and mentor Applied Scientists and software development engineers with a strong interest in and knowledge of ML. Your work will directly benefit customers and the Amazon Video business.
- MS. in Computer Science, Machine Learning, Operational Research, Statistics or a related quantitative field
- 5+ years of hands-on experience in predictive modeling and analysis
- Strong algorithm development experience
- Skills with Java, C++, or other programming language, as well as with R, MATLAB, Python or similar scripting language
The ideal candidate will have a PhD in Mathematics, Statistics, Machine Learning, or a related quantitative field, and 7+ years of relevant work experience, including:
- Significant peer reviewed scientific contributions in relevant field.
- Extensive experience applying theoretical models in an applied environment.
- Expertise on a broad set of ML approaches and techniques, ranging from Artificial Neural Networks to Bayesian Non-Parametrics methods.
- Strong Experience in Structured Prediction and Dimensionality Reduction.
- Expert in more than one more major programming languages (C++, Java, or similar) and at least one scripting language (Perl, Python, or similar).
- Proven track record of production achievements in language, search and personalization.
- Strong fundamentals in problem solving, algorithm design and complexity analysis.
- Strong personal interest in learning, researching, and creating new technologies with high commercial impact.
- Experience with defining organizational research and development practices in an industry setting.
- Proven track in leading, mentoring and growing teams of scientists (teams of five or more scientists).
- Strong communication and data presentation skills
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