• Study and transform data science prototypes • Solve complex problems with multilayered data sets, and optimize existing machine learning libraries and frameworks • Design machine learning systems • Research and implement appropriate ML algorithms and tools • Develop machine learning applications according to requirements • Run machine learning tests and experiments • Perform statistical analysis and fine-tuning using test results • Extend existing ML libraries and frameworks • Optimize machine learning algorithms for performance, scalability, and reliability • Stay updated with the latest machine learning techniques and technologies, and proactively identify opportunities to apply them in our context • Collaborate with data engineers and scientists to build efficient data pipelines for training and deploying machine learning models • Monitor and maintain the performance of deployed models, and iterate on them to continuously improve results