ML Data Engineer

Job description

DESCRIPTION

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 team within AWS provides opportunities to innovate in a fast-paced organization that contributes to game-changing projects and technologies that get deployed on devices and the cloud. As a ML Data Engineer, you'll partner with technology and business teams to build new services that surprise and delight our customers. You will be working with terabytes of text, images, and other types of data to solve real-world problems.

We're looking for top architects, system and software engineers capable of using ML and other techniques to design, evangelize, and implement state-of-the-art solutions for never-before-solved problems.

The primary responsibilities of this role are to:
· Design data architectures and data lakes
· Provide expertise in the development of ETL solutions on AWS
· Use ML tools, such as Amazon SageMaker Ground Truth (GT) to annotate data. Work with Professional Services on designing workflow and user interface for GT annotation.
· Collaborate with our data scientists to create scalable ML solutions for business problems
· Interact with customer directly to understand the business problem, help and aid them in implementation of their ML ecosystem
· Analyze and extract relevant information from large amounts of historical data — provide hands-on data wrangling expertise
· Work closely with account team, research scientist teams and product engineering teams to drive model implementations and new algorithms
This position requires travel of up to 25%.

Desired profile

BASIC QUALIFICATIONS

· This position requires that the candidate selected be a U.S. citizen and obtain and maintain an active Secret security clearance.
· BS in computer science, or related technical, math, or scientific field
· 5+ years of relevant experience in building large scale enterprise IT systems
· 3+ year of experience with data engineering, ETL, and data wrangling
· 1+ year of public cloud computing experience in AWS