Amazon is the 4th most popular site in the US (http://www.alexa.com/topsites/countries/US). Our product search engine is one of the most heavily used services in the world, indexes billions of products, and serves hundreds of millions of customers world-wide. We are working on a new AI-first initiative to re-architect and reinvent the way we do search through the use of extremely large scale next-generation deep learning techniques. Our goal is to make step function improvements in the use of advanced Machine Learning (ML) on very large scale datasets, specifically through the use of aggressive systems engineering and hardware accelerators. This is a rare opportunity to develop cutting edge ML solutions and apply them to a problem of this magnitude. Some exciting questions that we expect to answer over the next few years include:
- Can a focus on compilers and custom hardware help us accelerate model training and reduce hardware costs?
- Can combining supervised multi-task training with unsupervised training help us to improve model accuracy?
- Can we transfer our knowledge of the customer to every language and every locale ?
Please visit https://www.amazon.science for more information
- PhD degree with 4+ years of applied research experience or a Master's degree and 6+ years of experience of applied research experience
- 3+ years of experience in building machine learning models for business application
- Experience programming in Java, C++, Python or related language
- Master's degree in Computer Science, Electrical Engineering, or related disciplines - Coding proficiency in at least one modern programming language (Python, Java, C++, etc.) - Coding proficiency in at least one modern deep learning framework (PyTorch, Tensorflow, MXNet) - Current knowledge of deep learning concepts (e.g. transformer models, data parallelism, model parallelism, etc.)
- PhD in Computer Science, Electrical Engineering or related disciplines. - Experience with hardware accelerators (e.g. GPGPU, FPGA, TPU) - Experience with AWS services, and large-scale data processing frameworks like Spark etc. - Internship or work experience in software engineering, machine learning or similar - ML projects (e.g. Kaggle competitions, hackathons, etc.)
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.