About me 👋

My name is Adrien, a dedicated Software Engineer from Luxembourg, specializing in MLOps and data-intensive systems.

🚀 As a Senior MLOps Engineer, I architect, build, and implement comprehensive MLOps platforms from the ground up, primarily for enterprise clients in the financial sector. My core focus is on enabling robust, scalable, and automated machine learning lifecycles – from development and training through to deployment and monitoring in production.

Key areas of my MLOps expertise include:

• Designing cloud-agnostic infrastructure for AI model development and deployment (training & inference).
• Implementing automated provisioning of cloud resources and CI/CD pipelines for models and data.
• Integrating model registries (e.g., MLflow) and data versioning tools (e.g., DVC).
• Leveraging Kubernetes for scalable model deployment and developing custom gateways (Go) for enhanced security, monitoring, and load management.
• Optimizing data scientist workflows and managing on-premise GPU resources effectively.

My primary toolkit revolves around Python, Go, Kubernetes, Docker, Airflow, DVC, and various cloud provider services.

Interests & Continuous Learning ⚙️

My intellectual curiosity extends far beyond MLOps, with a deep-seated interest in infrastructure, deploying services, and system configuration. I get a real kick out of seeing things work seamlessly from the ground up, understanding the entire stack from memory optimization to continuous integration and deployment. This website is a testament to that — it's self-hosted on a home server, and you can find all the configurations and details of my setup here. I enjoy optimizing the stack, getting hands-on with the hardware, and ensuring everything fits together perfectly.

This enthusiasm for low-level systems and high performance drives my current learning endeavors in:

• Infrastructure & Self-Hosting: Dedicated to mastering the art of building, hosting, and maintaining efficient, reliable systems.
• High-Performance Computing (HPC): Delving into frameworks like OpenCL and CUDA to master parallel processing and harness GPU power.
• Memory Management: Exploring the nuances of manual and automatic memory allocation to craft truly great software.
• Systems Programming (Zig): Embracing Zig for its potential in performance-critical applications. My projects like the Advent of Code 2025 solutions (/adrien/Advent-of-Code) and ZipponDB (/adrien/ZipponDB) showcase my dedication to building efficient software from scratch. ZipponDB, in particular, is a database I've built entirely in Zig with no external dependencies, focused on simplicity, performance, and portability.
• Linux and Kernel Exploration: Now that I'm confident in my existing skills, I'm starting to investigate Linux internals and kernel programming to gain a foundational understanding of how operating systems truly function.
• Compilers, Assembly Language, and Hardware Architecture: Continuously investigating these areas to gain a fundamental understanding of system performance.

My ultimate goal is to leverage this comprehensive knowledge to architect and build exceptionally performant, resilient, and efficiently deployed software systems, bridging the gap between MLOps, HPC, and robust infrastructure.

🎯 My ambition is to lead the design of cutting-edge MLOps solutions and contribute to complex, performance-critical open-source projects, ideally in a remote capacity.
📅 I am committed to daily coding and continuous learning through technical literature and community engagement.
🎲 Fun fact: I can fall asleep in <1min every night.