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### Hi, I'm Adrien Charles Bouvais π
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# Adrien Bouvais
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I'm a Software Development Engineer who loves to design and build high-performance, scalable distributed systems from the ground up. My passion lies at the intersection of High-Performance Computing (HPC), low-level systems programming, and efficient ML infrastructure.
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Data & Platform Engineer based in Luxembourg.
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I design backend systems, data platforms, and inference infrastructure β currently architecting the backend for Clearstream AI at Clavem Group.
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---
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* π **I build:**
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## Work
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* [**ZipponDB**](https://git.bouvais.lu/adrien/ZipponDB): Database engine in Zig to master low-level data systems.
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* S3-Lite: Portable S3-compatible object storage in Zig & SQLite. (Still private for now)
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* [**Multi-Provider LLM Gateway**](https://git.bouvais.lu/adrien/Jade): Cost-optimized AI gateway in Go. (Old SaaS project)
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* [**Self-Hosted**](https://git.bouvais.lu/adrien/Selfhosted-config): My self-hosted services docker compose + config.
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* GPU-accelerated applications with **CUDA** and exploring **OpenCL**.
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* π§ **My Core Focus:**
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**Senior Data/ML Engineer β Clavem Group** *(2024 β present)*
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* **High-Performance Computing:** Optimizing code for massive parallelism with CUDA/OpenCL.
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Lead backend architect for a cloud-agnostic AI/data platform serving multiple business units in production.
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* **Low-Level Systems:** Building efficient, memory-safe software with Zig.
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- Designed full platform architecture: ingestion, storage, serving, and security layers
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* **Distributed ML Systems:** Architecting and building the infrastructure for scalable AI.
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- GitOps CI/CD on OpenShift/ArgoCD β config repos per environment, PR-gated promotion to production
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- Inference containers in Python, model/dataset registry via DVC + Artifactory, automated via GitHub Actions
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- Operated and monitored production workloads on OpenShift; enforced secrets management and least-privilege access
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* π« **How to reach me:**
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**Data Engineer β Reveals SA** *(2023 β 2024)*
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* **Email:** [contact@bouvais.lu](mailto:contact@bouvais.lu)
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Core banking data migration and quality platform for a Luxembourg bank.
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* **LinkedIn:** [www.linkedin.com/in/adrien-bouvais-717b04155](https://www.linkedin.com/in/adrien-bouvais-717b04155/)
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- Fault-tolerant pipeline migrating billions of rows of sensitive financial data β zero data loss, TLS-secured
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- Airflow DAGs for multi-source ETL: parallel tasks, dataset dependencies, Oracle β PostgreSQL consolidation
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- Real-time data quality platform (Python/Flask) and self-service SQL validation framework for non-technical stakeholders
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**Languages:** Go, Python, Zig
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**Data & AI Consultant β Ernst & Young** *(2022 β 2023)*
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Data architecture advisory for enterprise clients on Azure.
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- Designed data platform architectures and ETL pipelines for clients across multiple industries
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- SQL schema optimisation for analytical workloads; Airflow-orchestrated data flows on Azure
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---
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## Currently Building
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### [Zigma](https://git.bouvais.lu/adrien/zigma) β A Programming Language for Science
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Write physics equations as code. Zigma attaches **dimensions and units directly to variables** and resolves them at compile-time via Zig's `comptime` β so a unit mismatch is a compiler error, not a runtime catastrophe.
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```
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g = 9.81 m/sΒ²
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t = 0..10 s step 0.1
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v0 = 20.0 m/s
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y = (v0 * t) - (0.5 * g * t^2) // Zigma derives: y is in [meters]
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wrong = y + t // Compile-Time Error: Cannot add [Length] to [Time]
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```
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Zigma transpiles directly to Zig β C-level performance, automatic SIMD acceleration, zero runtime overhead. Supports uncertainty propagation (`20.0 +/- 0.5 m/s`), native CSV interpolation for empirical data, and `i128` precision for large-scale spatial simulations.
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Roadmap: WASM notebook, GPU acceleration (WebGPU), autograd, automatic Jacobian transforms.
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### [dimal](https://git.bouvais.lu/adrien/zig-dimal) β Dimensional Analysis Library for Zig
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The type system powering Zigma. A unified `Tensor` API parameterized entirely at compile-time:
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`T` (numeric type) Β· `dims` (physical dimensions) Β· `scales` (unit scale) Β· `shape` (array shape)
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Originally built to use `i128` positions in space simulations to avoid float precision loss at astronomical scales.
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---
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## Stack
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`Python` `Go` `Zig` `SQL` Β· `PostgreSQL` `Oracle` `SQLite`
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`OpenShift` `ArgoCD` `Airflow` `Terraform` `GCP` `Azure`
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`GitHub Actions` `DVC` `FastAPI` `Flask` `Docker`
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---
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`contact@bouvais.lu`
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