The talk focuses on simplifying/demystifying MLOps, encourages others to take steps to learn this powerful SE method. We also talked about Emmanuel's journey in ML engineering, the evolution of MLOps, daily life, and SE problems, and what's next in MLOps (fusion of AIOps, EU AI regulations impact on MLOps workflow, etc).
In this episode
Senior Machine Learning Engineer, TietoEvry
Emmanuel Raj is a Finland-based Senior Machine Learning Engineer. He is a passionate ML Researcher, Software engineer, speaker, and author. He is also a Machine Learning Engineer at TietoEvry and a Researcher at Arcada University of Applied Sciences in Finland. With over 6+ years of experience building ML solutions in the industry, he has worked on multiple domains such as Healthcare, Manufacturing, Finance, Retail, e-commerce, aviation, etc. Emmanuel is passionate about democratizing AI and bringing state-of-the-art research to the industry. He has a keen interest in R&D in technologies such as Edge AI, Blockchain, NLP, MLOps, and Robotics. He believes the best way to learn is to teach and he is passionate about teaching about new technologies, that's one reason for writing a book and making an online course on MLOps. Emmanuel is the author of the book "Engineering MLOps". The book covers industry best case practices and hands-on implementation to Rapidly build, test, and manage production-ready machine learning life cycles at scale. There is a big evolution happening in Data science for good, and we are moving away from notebooks and models sharing to a collaborative way of working via MLOps. We will discuss this big evolution of DevOps, MLOps, Data Engineering, Data Science, and Data-Driven business in the meetup.
Demetrios is one of the main organizers of the MLOps community and currently resides in a small town outside Frankfurt, Germany. He is an avid traveller who taught English as a second language to see the world and learn about new cultures. Demetrios fell into the Machine Learning Operations world, and since, has interviewed the leading names around MLOps, Data Science, and ML. Since diving into the nitty-gritty of Machine Learning Operations he felt a strong calling to explore the ethical issues surrounding ML. When he is not conducting interviews you can find him making stone stacking with his daughter in the woods or playing the ukulele by the campfire.