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Organization
Job Title
Senior Machine Learning Software Engineer - Linux/Unix, (CentOS, Ubuntu) and Mac OS
Location
Dublin Leinster,
Country
Ireland
Region
International
Reference Number
1700037X
Position type
Permanent
Category
Retail
Job Function
Engineering
Information Technology

Senior Machine Learning Software Engineer - Linux/Unix, (CentOS, Ubuntu) and Mac OS

Job Description

Machine Learning Software Engineer

You will be joining the Personalization and Machine Learning team to build the algorithms and services that customize the Gilt member experience from sale notifications to product recommendations.

We are an agile, product-driven, initiative-based team crafting the next generation of fashion personalization algorithms. We use our customer’s behavior to gain deeper insights into our members’ preferences, extract new information from product images and descriptions, and find the best ways to serve as personal stylists for our fashion-savvy customers.

You are a problem-solver -- preferring to use existing tools and techniques, but with the flexibility to suit them to the business problems at hand.

You will be designing and building large-scale statistical learning systems. You have experience with recommendations, predictions, or image classification, and with the machine learning frameworks to robustly build, validate, test, and monitor statistical models.

Qualifications

Today, you

  • understand the mechanics of training, cross-validating, regularizing, and evaluating statistical classifiers and supervised learning (e.g. logistic regression, boosted trees)
  • have an interest and maybe some experience with deep learning models such as convolutional neural networks or restricted boltzmann machines and understand different types of layers, loss functions, and backpropagation
  • develop code fluently in a functional, imperative, and object-oriented language (maybe Scala or Java).
  • Implement data-intensive, horizontally-scalable systems (Map-Reduce, Spark, etc.).
  • work with relational databases (we use PostgreSQL) and NoSQL databases (MongoDB, DynamoDB, Redis etc.)
  • communicate via RESTful APIs with HTTP and JSON.
  • use Linux/Unix, (CentOS, Ubuntu) and Mac OS.
  • continuously deploy with container technologies such as Docker.