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<h1 align="left">About me 👋</h1>
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<p align="left">My name is Adrien, a dedicated Software Engineer from Luxembourg, specializing in MLOps and data-intensive systems.</p>
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<p align="left">
🚀 As a <strong>Senior MLOps Engineer</strong>, 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.
<br><br>
Key areas of my MLOps expertise include:
<ul>
<li>Designing cloud-agnostic infrastructure for AI model development and deployment (training & inference).</li>
<li>Implementing automated provisioning of cloud resources and CI/CD pipelines for models and data.</li>
<li>Integrating model registries (e.g., MLflow) and data versioning tools (e.g., DVC).</li>
<li>Leveraging Kubernetes for scalable model deployment and developing custom gateways (Go) for enhanced security, monitoring, and load management.</li>
<li>Optimizing data scientist workflows and managing on-premise GPU resources effectively.</li>
</ul>
My primary toolkit revolves around Python, Go, Kubernetes, Docker, Airflow, DVC, and various cloud provider services.
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<h2 align="left">Interests & Continuous Learning ⚙️</h2>
<p align="left">
Beyond my professional MLOps work, I possess a strong intellectual curiosity for <strong>High-Performance Computing (HPC)</strong> and <strong>low-level systems programming</strong>. I am fascinated by the intricacies of how software interacts with hardware to achieve maximum efficiency.
<br><br>
This passion drives my current learning endeavors in:
<ul>
<li><strong>Zig:</strong> Exploring its potential for systems programming and performance-critical applications.</li>
<li><strong>Memory Management:</strong> Deepening my understanding of manual and automatic memory allocation strategies.</li>
<li><strong>Parallel Computing:</strong> Actively studying frameworks like OpenCL, CUDA, and potentially OpenGL for GPGPU, to harness parallel processing power.</li>
<li>Investigating compilers, assembly language, and hardware architecture to gain a foundational understanding of system performance.</li>
</ul>
My ultimate goal is to leverage this knowledge to build exceptionally performant and resilient software systems, potentially at the intersection of MLOps and HPC.
</p>
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<p align="left">
🎯 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.
<br>
📅 I am committed to daily coding and continuous learning through technical literature and community engagement.
<br>
🎲 Fun fact: I can fall asleep in <1min every night.
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