Pracovní náplň
Grebeňová Kateřina, e-mail: katerina.grebenova@galytix.com
Napln prace
- Develop a state-of-the-art data science and ML runtime stack in a multi-cloud environment.
- Understand and use computer science fundamentals, including data structures, algorithms, computability and complexity and computer architecture.
- Manage the infrastructure and pipelines needed to bring models and code into production.
- Demonstrate end-to-end understanding of applications (including, but not limited to, the machine learning algorithms) being created.
- Build algorithms based on statistical modelling procedures and build and maintain scalable machine learning solutions in production.
- Apply machine learning algorithms and libraries.
- Research and implement best practices to improve the existing machine learning infrastructure.
- Collaborate with data engineers, application programmers and data scientists.
Kvalifikace
- Qualification in some of the related fields such as computer science, statistics, electrical engineering, mathematics, or physical sciences.
- Self-starter with excellent communication/time management skills.
- Computer programming is a must, knowledge of Python.
- Experience scaling machine learning on data and compute grids.
- Proficiency with K8n, Docker, Linux and cloud computing.
- Experience with MLflow.
- MLOps, CI, Git and Agile processes.
- English language communication skills