The Amazon ML AU team is developing state-of-the-art, large-scale Machine Learning methods and applications involving terabytes of data. The group focuses on Deep Learning problems in Computer Vision and Natural Language Processing, with particular expertise in the intersection between these two fields, to a wide spectrum of areas such as Amazon Retail, Seller Services, and Online Video.
You will be responsible for building a team of scientists and developers who are experienced in taking an idea to reality – from prototype to a customer-facing product, their career development, as well as the road map definition and prioritization for the organization. You will be expected to be heavily entrepreneurial in style and be experienced to develop a business plan as well as dive deep in the scientific and technical details of the technology your team is building. This team also publish our research in the best venues internationally.
As part of this team, you will take on challenging, novel problems every day and collaborate with cross-functional teams. You'll need to be comfortable with a degree of ambiguity that’s higher than most projects and love the idea of solving problems that have never been solved before. You will provide thought leadership to technical and business leaders, and have a demonstrated ability to think strategically about business, product, and technical challenges.
- PhD in Computer Science, Mathematics, Statistics, or a related quantitative field.
- 10+ years industry experience building successful production software systems.
- 7+ years of applied research experience.
- Experience with one of the following areas: machine learning technologies, Reinforcement Learning, Deep Learning, Computer Vision, Natural Language Processing (NLP) and related applications.
- Proven ability to implement, operate, and deliver results via innovation at large scale.
- Experience communicating with executives and non-technical leaders.
- Strong Computer Science fundamentals in data structures, algorithm design, statistics and system design.
- Significant peer reviewed scientific contributions in Reinforcement Learning, Deep Learning, Computer Vision, Natural Language Processing, or related 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.
- Expert in more than one more major programming languages (C++, Java, or similar) and at least one scripting language (Python or similar).
- 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 scientist).
- 10+ years of industry experience in applying Machine Learning.