As a Machine Learning Engineer in DataRobot, you will work on our machine learning platform & actively contribute to the automation of data science best practices & the development of our state-of-the-art preprocessing, modeling & reporting capabilities.
We are looking for talented people with excellent engineering skills & deep knowledge of Machine Learning who can analyze problems, develop innovative generalized solutions, & implement them for real-world use on top of our platform.
DataRobot is based around delivering best-in-class data science solutions & this position provides the opportunity to build key data science components of our system.
- Design & build next-generation machine learning frameworks
- Build interfaces that make it easy to write good data-science code & hard to take dangerous shortcuts
- 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