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
- 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
- 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