Capable of deploying and managing applications on Kubernetes. Deployed, and managed, many machine learning model containers.
Experience with writing dockerized containers. Examples of usages are for REST APIs or for productionizing Machine Learning models.
Capable of creating Prometheus metrics. Also experienced with creating alarms for metrics using PromQL and AlertManager and performance graphs for Grafana.
I use git as a Version Control system both at work and in home-projects. I am using Github as my code backup store for home-projects. For work-related projects I use either Github of Gitlab.
During my study Data Science I’ve learned many different Machine Learning techniques. I am experienced in developing Neural Networks, recommendation systems such as a collaborative filter and different types of clustering algorithms.
I have used the Python API PySpark on datasets of close to 1TB. Using PySpark I created different predictive models, such as the built-in Collaborative Filter. I also used PySpark to analyze models that went into production.
I have experience writing Neural Networks in both the low-level Python API of Tensorflow as well as its high-level API using Keras.
During my time at Primed IO I have had the opportunity to extend my knowledge to the field of Software Engineering. Together with my knowledge in the field of Data Science, I am now able to productionize Machine Learning models.
I use Python as my main programming language. I have experience with popular libraries such as SciPy, Pandas, NumPy, PyTorch and Matplotlib.
Golang I use as the main language for professional development. I am capable of writing scalable, testable, and maintainable programs.