MLOps Engineer

Industry: Retail
Remote
Company size: 1-10
Full-time/Part-time

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Job description

A fast-growing company that is helping retailers to expand their online secondhand stores without the inconvenience of listing, is looking for a MLOps Engineer. The engineer will be responsible for determining any problems that could hinder the company from utilizing its information assets to their full potential. The company is making it easier for businesses to easily focus on sourcing and selling their products more efficiently. This is an exciting opportunity for candidates who are eager to test their skills while working in a dynamic, challenging environment. 

 

Job Responsibilities:

  • Use semi-supervised learning and few-shot learning to remove photos from unlabeled clothing data before training your classification model
  • Create a highly accurate classification model utilizing semi-supervised learning techniques on real-world apparel data by filtering out (un-labeled data) and manually labeling the dataset
  • Ensure high-accuracy brand and size determination from a product tag image
  • Find techniques to obtain fresh data sources, then evaluate their reliability

Job Requirements:

  • Bachelor’s/Master’s degree in Engineering, Computer Science (or equivalent experience)
  • At least 3+ years of relevant experience as an MLOps Engineer
  • Prolific experience working on building models in PyTorch
  • Demonstrable experience with MERN stack and GCP
  • Extensive knowledge and experience developing and testing major APIs
  • Nice to have some DevOps experience
  • Great English communication skills, both spoken and written 

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In a nutshell, Turing aims to make the world flat for opportunity. Turing is the brainchild of serial A.I. entrepreneurs Jonathan and Vijay, whose previous successfully-acquired AI firm was powered by exceptional remote talent. Also part of Turing’s band of innovators are high-profile investors, such as Facebook's first CTO (Adam D'Angelo), executives from Google, Amazon, Twitter, and Foundation Capital.

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