Machine learning (ML) has been strategic to Amazon from the early years. We are pioneers in areas such as recommendation engines, product search, eCommerce fraud detection, and large-scale optimization of fulfillment center operations.
The Amazon ML Solutions Lab team helps AWS customers accelerate the use of machine learning to solve business and operational challenges and promote innovation in their organization. As an ML Solutions Lab data scientist, you are proficient in designing and developing advanced ML models to solve diverse challenges and opportunities. You will be working with terabytes of text, images, and other types of data to solve real-world problems. You'll design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience.
We're looking for talented data scientists capable of applying classical ML algorithms and cutting-edge deep learning (DL) and reinforcement learning approaches to areas such as drug discovery, customer segmentation, fraud prevention, capacity planning, predictive maintenance, pricing optimization, call center analytics, player pose estimation, event detection, and virtual assistant among others.
The primary responsibilities of this role are to:
Design, develop, and evaluate innovative ML/DL models to solve diverse challenges and opportunities across industries
Interact with customer directly to understand their business problems, and help them with defining and implementing scalable ML/DL solutions to solve them
Work closely with account teams, research scientist teams, and product engineering teams to drive model implementations and new algorithms
This position requires travel of up to 25%, and can be located in Austin, Chicago, New York, Boston, Washington D.C., Atlanta, Palo Alto/Bay Area, or Seattle.