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DataRobot // machine learning automation software for enterprise
Engineering, Full Time    Boston, United States    Posted: Wednesday, November 20, 2019
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Job Summary

As a Machine Learning Engineer on our Core Modeling team, you will work on DataRobots machine learning platform & actively contribute to the development of our state-of-the-art preprocessing & modeling capabilities.

Core Modeling owns the entire data science backend for DataRobot, & is responsible for making sure our models & modeling automation are the best in the world.

We are looking for talented people with excellent engineering skills & deep knowledge of machine learning who can analyze problems, design unprecedented solutions, & implement them for real-world use on top of our platform.

DataRobot is based around delivering best-in-class AI solutions, & this position provides the opportunity to build the key machine learning components of our system.


  • Automate machine learning processes
  • Design & build machine learning models for accuracy & scalability
  • Integrate machine learning algorithms with other applications & services

Main Requirements

  • Recommended background: 5+ years of combined Python engineering & machine learning experience
  • Experience writing maintainable, testable, production-grade Python code
  • Understanding of different machine learning algorithm families & their tradeoffs (linear, tree-based, kernel-based, neural networks, unsupervised algorithms, etc.)
  • Good command of scientific Python toolkit (numpy, scipy, pandas, scikit-learn)
  • Understanding of time, RAM, & I/O scalability aspects of data science applications (e.g. CPU & GPU acceleration, operations on sparse arrays, model serialization & caching)
  • Software design & peer code review skills
  • Experience with automated testing & test-driven development in Python
  • Experience with Git + GitHub
  • Comfortable with Linux-based operating systems

Desired Skills

  • Experience with large-scale machine learning (100GB+ datasets)
  • Experience with deep learning libraries & frameworks (TensorFlow, Keras, PyTorch etc.)
  • Competitive machine learning experience (e.g. Kaggle)
  • Previous experience of deploying & maintaining machine learning models in production
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