Offers “Amazon”

Expires soon Amazon

Deep Learning Architect, ML Solutions Lab

  • Delhi, India
  • Studies / Statistics / Data

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 ML team within Amazon Internet Services Private Limited (“AISPL”) 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 Deep Learning Architect in AISPL, you'll partner with business and other support teams of AISPL 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 in AISPL 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:
· Use ML tools, such as Amazon SageMaker and Amazon Simple Storage Service, to provide a scalable cloud environment for our customers to label data, build, train, tune and deploy their models
· Collaborate with our data scientists to create scalable ML solutions for business problems
· Interact with AISPL 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 to help automate and optimize key processes
· Work closely with account team, research scientist teams and product engineering teams to drive model implementations and new algorithms

Desired profile



BASIC QUALIFICATIONS

· BS in computer science, or related technical, math, or scientific field
· 5+ years of professional experience in a business environment
· 5+ years of relevant experience in building large scale enterprise IT systems
· 1+ year of public cloud computing experience in AWS Cloud
· 1+ year of experience hosting and deploying ML solutions (e.g., for training, tuning, and inferences)

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