Oryan Omer
Principal Software Engineer 👨🏻💻 | MLOps Engineer 🤖 | ML Engineer 🤖 | Cyber Security Specialist | Wave Surfer 🌊
Principal Software Engineer with a strong expertise in machine learning, MLOps, and Cloud Security.
With 10 years of experience developing services for both production and development environments, I have a proven track record of delivering high-quality software solutions.
Throughout my career, I have led teams, mentored junior and senior developers, improved R&D processes, designed complex architecture solutions, and managed large-scale projects.
Additionally, I have been a speaker at several conferences such as ODSC West(SF) and Europe(London) in 2022, Google Next 24 in Las Vegas, and have also participated in various webinars.
I frequently publish content on Linkedin and Medium that talks about ML engineering, MLOps, Software engineering, and tech in general.
I have a B.sc computer science from the College of Management.
In my free time, I'm surfing 🌊, snowboarding 🏂 and doing a lot of sports (:
Activities
In the following list, you will find some events and webinars where I have given a talk
Blogs
A few of my published articles can be found here.
Data-driven retraining with production observability insights
“Refreshing” a model’s training observations isn't always enough to predict future results better. Using observability of model production data gives us a clear path to better decisions on our retraining strategies.
So you want to be API-first?
Building a great, scalable, and easy-to-integrate product starts with design. At superwise, we understand the importance of being an API-first company. Read my article and follow superwise’s journey to API-first and what considerations you should make before embarking on that journey.
Testing Data-driven Microservices
Testing microservices that work on a massive data scale is a complex task. I designed an efficient architecture to make the testing phase much easier for writing, debugging and ensuring the application integrity (Hint: It leverages Jupyter Notebook and Papermill)
Use FastAPI for Better Machine Learning in Production
Deploying ML for serving in production sounds like a complicated task, which costs too much times for developers. Check out my article to understand why you should start using FastAPI to speed up this process and save a lot of time.
Scaling data-driven microservices
Scaling data-driven microservices need to be supported by an infrastructure that can accommodate resource extension or decrease resources, but more importantly, codes should be written to support scalability
CONTACT ME TO GET STARTED