Research Engineering Intern

4 Days ago • Upto 1 Years • Research & Development • Artificial Intelligence

Job Summary

Job Description

This Research Engineering Internship at Microsoft Research AI for Science focuses on applying deep learning to solve fundamental challenges in molecular sciences. The intern will work on language modeling within the context of natural sciences, architecting, designing, and implementing scalable solutions for machine learning research involving large datasets. Responsibilities include building and optimizing distributed data processing pipelines, developing tools for building, training, and scaling machine learning models. The ideal candidate has a strong understanding of machine learning, language modeling, and experience with Linux and scientific computing. Experience with cloud computing or HPC is a plus. This internship is located in Amsterdam, Netherlands.
Must have:
  • Bachelor's or Master's degree in relevant field
  • Strong Linux and open-source experience
  • Understanding of machine learning fundamentals
  • Scientific computing experience
  • Build scalable ML solutions
  • Develop data processing pipelines
Good to have:
  • Cloud computing or HPC experience
  • Language modelling experience

Job Details

Overview

Deep learning has only just started its transformative impact on the natural sciences. In Microsoft Research AI for Science we are seeking to solve some of the fundamental challenges in the molecular sciences with deep learning. 

 

We are seeking a highly motivated Research Engineering Intern. The ideal candidate will have an understanding of machine learning and/or language modelling fundamentals, and will work on language modelling within the context of natural sciences. 

Qualifications

Required/Minimum Qualifications: 

  1. Working towards a Bachelor’s or Master's degree or equivalent work experience in Computer Science, Physics, Engineering, Chemistry, Mathematics or a related field. 
  1. Strong familiarity with Linux and the open-source ecosystem 
  1. Experience with scientific computing 

 

Preferred/Additional Qualifications: 

  1. Experience with cloud computing or HPC is a plus 
  1. Experience with language modelling is a plus 

 

Responsibilities

  1. Architect, design, and implement scalable and robust solutions for machine learning and scientific research involving large volumes of heterogeneous data. 
  1. Build and optimize distributed data processing and model building pipelines. 
  2. Develop and maintain tools and technologies for building, training, optimizing, scaling machine learning solutions 

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