Machine Learning Ops Engineer

Industry: Advertising
Company size: 11-50

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Job description

A fast-growing US-based company active in the advertising space is looking for a Machine Learning Ops Engineer. The engineer will design, build and deploy ML pipelines using various AI platforms. The AI-powered machine learning tool is uniquely designed to create and deliver effective marketing creatives in any format. This job offers a sound opportunity for engineers to rub shoulders with highly skilled and experienced professionals while showcasing their skills. 


Job Responsibilities:

  • Work on designing, building, and deploying ML pipelines using resources like Airflow, Python, Kubeflow, Vertex AI, etc.
  • Monitor models under development for model evaluation 
  • Deploy models within GCP. 
  • Work with tools for scheduling or automating execution of processes advantageous 
  • Reduce the time required to make a change to a model in production 

Job Requirements:

  • Bachelor’s/Master’s degree in Engineering, Computer Science (or equivalent experience)
  • At least 3+ years of relevant experience as a machine learning engineer
  • Expertise in working on machine learning platforms
  • Thorough knowledge of ML and AI platforms along with Kubeflow
  • Ability to work with languages like Python and SQL
  • Understanding of Docker and Kubernetes
  • Ability to work on Big Query 
  • Knowledge of DevOps processes
  • Thorough understanding of Google Cloud Platform

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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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