Deep Learning Engineer, Core Modeling
As a Deep Learning Engineer on our Core Modeling team, you will work on our machine learning platform and actively contribute to the development of our state-of-the-art preprocessing and modeling capabilities.
Core Modeling owns the entire data science backend for DataRobot and is responsible for making sure our models and modeling automation are the best in the world.
We are looking for talented people with excellent engineering skills and deep knowledge of Machine Learning who can analyze problems, develop innovative solutions, and implement them for real-world use on top of our platform.
DataRobot is based around delivering best-in-class data science solutions and this position provides the opportunity to build the key data science components of our system focusing on Deep Learning.
- Automate machine learning processes
- Design and build machine learning models for scalability and accuracy
- Work on development in the following areas: Image/Video, Text and Audio processing
- 5 years of combined python Engineering / Data Science experience:
- Engineering experience
- Data Science experience
- Deep Learning experience
- Experience writing maintainable, testable, production-grade Python code
- Good command of scientific Python toolkit (numpy, scipy, pandas, scikit-learn)
- Understanding of different machine learning algorithm families and their tradeoffs (linear, tree-based, kernel-based, neural networks, unsupervised algorithms, etc.)
- 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
- Proficiency in Deep Learning Frameworks( Keras, Tensorflow, Pytorch, Caffe, Mxnet etc.)
- Experience in semi-supervised/transfer learning
- Experience working in image/video processing, NLP, time-series signal processing, or audio processing is a plus
- Contribution to open-source data-science/deep-learning packages
- Competitive machine learning experience (e.g. Kaggle)
- Previous experience of deploying and maintaining machine learning models in production