Machine Learning Engineer

Industry: Pharma
Remote
Company size: 251-10K
Full-time
Not disclosed

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Job description

A NASDAQ-listed century-old pharmaceutical multi-billion dollar giant, operating in over 60+ countries, is looking for a Machine Learning Engineer. The developer will be using machine learning techniques to power AI-based applications and handling the complete end-to-end machine learning lifecycle. The global company is listed in the Fortune 500 in terms of revenue and has a top prime credit rating. This is a rare opportunity for developers to work with a global, industry-leading company with a net worth of over $435 billion. 

 

Job Responsibilities:

  • Design and develop highly scalable models/tools/classifiers/algorithms with the help of AI and Machine Learning principles and techniques 
  • Work closely with the existing team of ML engineers, data scientists, and product managers to further develop the product’s capabilities
  • Break down a complex task into smaller steps and anticipate what edge cases might have been ignored
  • Guide and mentor team members while bringing extensive knowledge of resources for training and mentorship

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
  • In-depth knowledge of Machine Learning technologies and frameworks
  • Prolific Deep Learning experience
  • Solid understanding and skilled with Python
  • Extensive ML project experience and strong fundamentals
  • Strong interpersonal and documentation skills
  • Excellent written and verbal English communication skills

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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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