Principal Deep Learning Engineer

Job Description

Posted on: 
July 24, 2023

As a Principal Machine Learning Engineer, you will work on DataRobot’s machine learning platform and actively contribute to the strategy, planning, and development of our Deep Learning and Generative product development, along with our other modeling capabilities.

We are looking for talented people with excellent engineering skills and deep knowledge of machine learning who can analyze problems, design unprecedented solutions, and implement them for real-world use on top of our platform. Our Principal engineers are also depended upon to lift up everyone around them and contribute to the excellence of every engineer in the organization.

You will be a key technical leader in our journey to be the best platform for extracting value from Deep Learning & Generative AI.


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

Job Requirements

  • Recommended background: 8-10+ years of combined Python engineering and machine learning experience - with a focus on Deep Learning techniques.
  • Experience as a technical leader capable of leading a team from idea to production software.
  • Experience with deep learning libraries and frameworks (TensorFlow, Keras, PyTorch etc.)
  • Experience writing maintainable, testable, production-grade Python code
  • Understanding of different machine learning approaches and their tradeoffs
  • Good command of scientific Python toolkit (numpy, scipy, pandas, scikit-learn)
  • Understanding of time, RAM, and I/O scalability aspects of data science applications (e.g. CPU and GPU acceleration, operations on sparse arrays, model serialization, and caching)
  • Software design and peer code review skills
  • Experience with automated testing and 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)
  • Competitive machine learning experience (e.g. Kaggle)
  • Previous experience in deploying and maintaining machine learning models in production

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