I am a Machine Learning Engineer with extensive experience in Python and PyTorch, currently focused on automating Machine Learning pipelines using tools such as Docker and MLFlow. In my role, I train ML and vision models, leveraging MLOps practices to streamline and optimize workflows. Additionally, I handle development tools by setting up Docker-based devcontainers to ensure smooth onboarding and collaboration.
With a background in Electrical & Electronics Engineering and strong skills in mathematics and programming, I bridge the gap between Machine Learning and iOS development projects. I am committed to leveraging technology to create high-performance, intelligent solutions and continuously seek opportunities to incorporate innovative AI/ML advancements into my work. In my free time, I am exploring the Mojo Programming Language to enhance my development skills and expand my technical expertise.
- Machine Learning Automation: Utilizing Docker and MLFlow to streamline ML workflows.
- ML & Vision Model Training: Developing and training machine learning and computer vision models using Python and PyTorch.
- MLOps Practices: Applying MLOps best practices to ensure efficient deployment, monitoring, and maintenance of ML models.
- Development Tools Management: Setting up Docker-based devcontainers for smooth onboarding and collaboration.
- iOS Development: Building robust and user-friendly mobile applications with Swift and Objective-C.
- Technical Foundation: Electrical & Electronics Engineering background with strong analytical and programming skills.
- Continuous Learning: Staying updated with the latest developments in AI, ML, and mobile technologies.
