Applied Scientist, Search M5

Palo Alto, California, USA

Applications have closed

Amazon.com

Free shipping on millions of items. Get the best of Shopping and Entertainment with Prime. Enjoy low prices and great deals on the largest selection of everyday essentials and other products, including fashion, home, beauty, electronics, Alexa...

View company page

Job summary


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 ?
This is a unique opportunity to get in on the ground floor, shape, and build the next-generation of Amazon Search. We are looking for exceptional scientists and ML engineers who are passionate about innovation and impact, and want to work in a team with a startup culture within a larger organization.
Please visit https://www.amazon.science for more information




Basic Qualifications


  • PhD or equivalent Master's Degree plus 4+ years of experience in CS, CE, ML or related field
  • 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.)

Preferred Qualifications

  • 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.

Tags: AWS Computer Science Deep Learning Engineering Machine Learning Model training MXNet PhD Python PyTorch Spark TensorFlow

Perks/benefits: Startup environment

Region: North America
Country: United States
Job stats:  9  0  0
Category: Data Science Jobs

More jobs like this

Explore more AI, ML, Data Science career opportunities

Find even more open roles in Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), Computer Vision (CV), Data Engineering, Data Analytics, Big Data, and Data Science in general - ordered by popularity of job title or skills, toolset and products used - below.