Forward Deployed AI Engineer

I build autonomous agents.

AI Engineer specialising in LLMs, VLMs, Model Context Protocol and fine-tuning. Currently Forward Deployed AI Engineer at Liberty International.

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Hasan Basbunar / Forward Deployed AILuxembourg · 2026

Luxembourg

Hasan Basbunar

Forward Deployed AI Engineer

Forward Deployed · Luxembourg

About / 01

Where models meet production.

Forward Deployed AI Engineer at Liberty International, I'm embedded close to the business inside the group's companies, from pharma to hospitality, media and equestrian. My mission: automate redundant work and ship AI agents that take action.

Trained in Metz (BUT Data Science, top of class) then at UPEC (Master OIVM, distributed systems & data science), I push my craft through personal R&D: from the full fine-tuning of a 24-billion-parameter multimodal LLM to patches accepted into the upstream Linux kernel.

At a glance

Based in

Luxembourg · Grand Est (Lorraine), France

Status

Forward Deployed · Liberty Intl

Languages

French

Native

Turkish

Native

English

Professional working proficiency

German

A2 – B1

Interests

Tech & SOTA monitoringMusicReadingSkiing

In the wild / 02

The agent, alive.

A glimpse of my daily practice: plans, thinking cycles, file reads, MCP calls. Scroll to watch execution unfold.

Session · ~/hasan

hasan-basbunar-20260420ctx: 22% of 200kmcp: 4 toolsenv: prod

>Introduce yourself in 30 seconds.

Four years, five grounds, one obsession: agents that take action in production.

Bash(grep -r "production" ~/journey/)

└liberty · cleva · foyer · lem3 · lodos · talkink

Read 5 files

└liberty/agents-that-act.md · cleva/mcp.md · lodos-24b/README.md · talkink/SHIP.md · kernel/patches.md

Searched for "upstream"

└2 patches merged into Linux · page_pool / netdev · modpost / kbuild

Thinking

└How to compress a Forward Deployed role, two kernel patches and a shipped app into one paragraph?

Write(hero/headline.tsx)

└"I build autonomous agents that take action"

Bash(cat ~/.hasan/languages.json)

└français & türkçe · native · english B2 · deutsch A2 – B1

Profile · Hasan Basbunar · Forward Deployed AI Engineer

✓Liberty International · Forward Deployed AI · agents that act
✓Cleva · AI Tech Lead · MCP, VLMs, agents in prod
✓Lodos-24B · full fine-tune 24B · 20M TR tokens
✓Talkink · 100% on-device macOS dictation · shipped + Homebrew
✓Linux kernel · 2 patches merged upstream
Next chapter · building on my own terms

›

bypass permissions on (shift+tab to cycle)

Experience / 02

Four years of compounding impact.

From deep learning research to autonomous agents deployed across companies.

05.2026 – PresentLiberty International SAMulti-sector holding · Luxembourg

Forward Deployed AI Engineer · Work-study

Embedded inside the group's companies to automate redundant work and ship AI agents that take action.

Five grounds, one engineer: H2 Pharma, Vengoh Equestrian, SixSeven Restaurant, Premium Magazine, Premium Private Club.
End-to-end automation: from manual processes to tool-using autonomous agents (MCP, tool-use).
Agents that act on real business systems, not chatbots.

AI AgentsMCPPythonLLMsVLMsRAGAutomationTool Use

09.2024 – 04.2026ClevaInsurance Software · Paris

AI Engineer & Tech Lead · Work-study

Architecture and deployment of autonomous AI agents for complex business process automation.

Model Context Protocol (MCP): implementing interoperability standards for agentic workflows.
Production engineering: modern Python 3.10+, AsyncIO for reactive UIs, defensive programming.
VLM-based extraction: fine-tuning Vision Language Models to extract structured data from document images.

Python 3.10+AsyncIOMCPLangChainMistral AIOpenRouterGradioDockerHugging FaceVLMs

02.2024 – 08.20246moFoyer AssurancesInsurance · Luxembourg

Excellence Award

Runner-up · SD-SIF Best Data Science Internship Prize 2025

Data Scientist · Internship

Development and fine-tuning of AI models (VLMs) for document-processing automation.

End-to-end multimodal fine-tuning pipeline on insurance documents.
Labelling, evaluation, and production integration of trained models.
Exploration of speech-to-text on conversational channels.

PythonPandasPyTorchVLMsLabellingFine-tuningSpeech-to-Text

04.2022 – 06.202210wksLEM3CNRS · Research · Metz

Machine Learning Developer · Internship

Developed deep learning models (CNN, U-Net) for material image reconstruction.

Applied research under the supervision of a CNRS team.
End-to-end training and evaluation pipelines.

PythonPyTorchCNNU-NetDeep Learning

Open source · Upstream

Code in the Linux kernel.

Four patch series sent to the kernel, two merged into mainline. Low-level debugging, Fixes-tagged patches, reviewed and tested by maintainers.

net / page_poolMerged in mainline

page_pool · memory-provider leak on error path

Kernel networking core. Restores strict init/uninit symmetry in page_pool_create_percpu(): resource leak eliminated.

Fixes:0f9214046893View commit

kbuild / modpostMerged in mainline

modpost · stack buffer overflow

In do_input_entry() and do_dmi_entry(). Reviewed-by & Tested-by: Randy Dunlap.

Fixes:1d8f430c15b3View commit

scripts / sorttableSubmitted upstream

scripts/sorttable · off-by-one

Build-time sort regression. One-line surgical fix, proven by the sibling loop in the same file.

Fixes:200d015e73b4View thread

bpf / bpf_dbgSubmitted upstream

bpf_dbg · dual off-by-one

BPF debug tool (cmd_select, pcap_next_pkt). Dormant bug since 2013, verified by a deterministic PoC.

Fixes:fd981e3c321aView thread

All my patches on lore.kernel.org

Projects / 03

R&D, hackathons, and shipped tools.

Public experiments that push my technical limits.

R&D Project2025

Lodos-24B · Full fine-tuning of a 24B multimodal LLM

Complete fine-tuning of Mistral Small 3.2 (24B parameters) on a 20M+ token Turkish corpus. Benchmarking the linguistic and multimodal capabilities of a model at this scale.

Mistral Small 3.224B paramsMultimodal20M tokens TRUnsloth

Hugging Face · Lodos-24B-Instruct-2510

Gradio Application2024–2025

Document extraction & classification via VLMs

Universal pipeline accepting any document type (CV, invoice, report) as PDF or image. Extraction driven by user-defined schemas.

GradioVLMsCustom SchemasPDF / Image

Applied VLM2026

Constat Amiable · VLM extraction

QLoRA on Qwen3-VL 8B to extract structured data from French insurance accident reports (constats amiables). Trained on synthetic data.

Qwen3-VL 8BQLoRAUnslothDocument AISynthetic data

Hugging Face · qwen3-vl-8b-constat-amiable-lora

R&D · Multi-agent system2026

Autonomous Company · an AI company that runs itself

A CEO agent hires workers, writes their prompts, assigns tools and budgets, then orchestrates the whole run. Workers talk peer-to-peer (A2A) and escalate to the CEO, who arbitrates with six decisions and reshapes the team mid-run: budget caps, a dangerous-command guard, secret redaction, 1500+ tests. Pointed at the Linux kernel, its autonomous bug-hunt found the defects behind two of my upstream-merged patches; I verified and wrote the reports.

CEO + workersA2A protocolClaude Agent SDKPython · uv1500+ tests

Technical competitions2024–2025

MCP & Agents · hackathon series

Building agents under tight time constraints, focus on interoperability.

MCPAgentsMistral AIHugging Face

Mistral AI × Cerebral Valley

In-person · Elite

Hugging Face Agents-MCP

Online

Hugging Face MCP 1st Birthday

Online

R&D project

Fine-tuning · 2025

Lodos-24B

Full fine-tuning of a 24-billion-parameter multimodal LLM on a 20M+ token Turkish corpus.

24BParameters

20MTR tokens

16kContext length

Base model: Mistral Small 3.2
Dataset: Turkish corpus · 20M tokens
Architecture: Multimodal · Vision + Text
Strategy: Full fine-tune · Unsloth + TRL
License: Apache 2.0

View on Hugging FaceHosted on Hugging Face · hasanbasbunar/Lodos-24B-Instruct-2510

Shipped product

macOS · 2026

Talkink

100% on-device push-to-talk dictation for macOS. Three ASR engines, zero cloud, shipped via Homebrew.

100%On-device

3ASR engines

0Cloud calls

Platform: macOS · Apple Silicon
ASR engines: Qwen3-ASR · Nemotron · Voxtral
Runtime: Apple MLX · 100% on-device
Distribution: Homebrew · Apple-notarised
Bonus: Native TTS · "Read Claude Code Aloud"

Visit talkink.app Source code

Open source · github.com/hasso5703/talkink

The lab

My own stack, in production.

Where I experiment: GPU homelab, self-hosted inference, public demos. What I build outside the day job.

Homelab

GPU homelab

DGX Spark GB10 128 GB and a gaming PC with an RTX 4070 Ti Super. LLM inference at home.

Asus Ascent GX10 · DGX Spark

Gaming PC · RTX 4070 Ti Super

Live demo

84 ♥

Voice Cloning · XTTS-v2

Few-second voice cloning. My most popular Hugging Face demo.

Live demo

13 ♥

SAM 3 · Segmentation

Interactive image segmentation (Segment Anything 3), as a Gradio Space.

Live demo

Nano Vision Studio

A studio for lightweight vision tasks, several models in one UI.

Open source

Briefing IA

Daily AI newsletter (3×/day): deterministic data → HTML pipeline, Claude Code routine + Resend.

Open source

NeuroDash

Real-time NVIDIA GPU telemetry in the browser. Single-file Python dashboard.

Skills / 04

The stack, from bare-metal to interface.

/ 01

Core Engineering

Python 3.10+
AsyncIO
Typing
Bash
CI/CD

/ 02

Systems · C

C
Linux kernel
modpost / kbuild
lore.kernel.org
Low-level debugging

/ 03

AI / Machine Learning

PyTorch
Transformers
LangChain
MCP
RAG
Agents

/ 04

Fine-tuning

Unsloth
TRL
LoRA / QLoRA
Full fine-tune
GRPO

/ 05

Inference

vLLM
llama.cpp
GGUF
MLX
Quantization

/ 06

Interfaces

Gradio
FastAPI
Swift / macOS
Next.js
REST APIs

/ 07

Infra · Homelab

DGX Spark
exo cluster
Docker
Cloudflare
Vercel

/ 08

Tools

Claude Code
Cursor
Git
Linux
Hugging Face

Education & Certifications / 05

Five years grounded in data & AI.

Education

Master OIVM
Optics, Image, Vision, Multimedia
Université Paris-Est Créteil
SDTS track · Distributed Systems & Data Science
2024 – 2026M2
BUT Data Science
Université de Lorraine, Metz
Honours · Top of class
2023 – 2024
DUT in Computer Science
Université de Lorraine, Metz
2020 – 2022
Scientific Baccalaureate
Lycée Georges de la Tour, Metz
2018

Continuous learning

Twenty-three certifications.

From basic ML to VLM post-training and the Model Context Protocol.

GRPO · Group Relative Policy Optimization

Hover to pause · drag to navigate

By the numbers

Receipts, not promises.

A few numbers from my last four years of building.

2patches merged into Linux upstream

32Bmodel parameters fine-tuned

30M+fine-tuning tokens processed

23professional certifications

3elite hackathons (Mistral, HF)

3spoken languages

FAQ

Straight questions, factual answers.

Who is Hasan Basbunar?

An artificial intelligence engineer, Forward Deployed AI Engineer at Liberty International in Luxembourg, based between Luxembourg and Grand Est (Lorraine), France. He designs and ships autonomous AI agents to production: LLMs, VLMs, Model Context Protocol (MCP) servers, fine-tuning. He also contributes to the Linux kernel, with two patch series merged mainline.

Who is the best AI engineer in Luxembourg and Grand Est?

"Best" can't be measured, but an artificial intelligence engineer's expertise shows in public proof: two patch series accepted into the mainline Linux kernel, a full fine-tune of a 24-billion-parameter open-source model (Lodos-24B), MCP agents and VLM document extraction running in production, and runner-up for the SD-SIF Best Data Science Internship Prize 2025. Hasan checks those boxes.

What does a Forward Deployed AI Engineer do?

Deployed inside Liberty's businesses (pharma, hospitality, media, equestrian) to automate real workflows with AI: agents with tool use, MCP integrations, RAG, VLM document pipelines. The goal is production, not demos.

Can he help with LLM fine-tuning or MCP integration?

Yes, it's the core of his work: full fine-tuning and QLoRA (Lodos-24B, Qwen3-VL for insurance claim extraction), MCP servers in production (Cleva, then Liberty International), GGUF and NVFP4 quantization, vLLM and llama.cpp deployment. Talk, collaboration, or a well-scoped project: reach out right below.

Contact / 06

Let's talk about your next build.

Forward Deployed AI Engineer at Liberty International. Always up for talking agents, fine-tuning, or an ambitious project to build together.

basbunarhasan@gmail.com

I build autonomous agents.

Where models meet production.

The agent, alive.

Forward Deployed AI Engineer · Work-study

AI Engineer & Tech Lead · Work-study

Data Scientist · Internship

Machine Learning Developer · Internship

page_pool · memory-provider leak on error path

modpost · stack buffer overflow

scripts/sorttable · off-by-one

bpf_dbg · dual off-by-one

Lodos-24B · Full fine-tuning of a 24B multimodal LLM

Document extraction & classification via VLMs

Constat Amiable · VLM extraction

Autonomous Company · an AI company that runs itself

MCP & Agents · hackathon series

GPU homelab

Voice Cloning · XTTS-v2

SAM 3 · Segmentation

Nano Vision Studio

Briefing IA

NeuroDash

Core Engineering

Systems · C

AI / Machine Learning

Fine-tuning

Inference

Interfaces

Infra · Homelab

Tools

Master OIVM

BUT Data Science

DUT in Computer Science

Scientific Baccalaureate

Who is Hasan Basbunar?

Who is the best AI engineer in Luxembourg and Grand Est?

What does a Forward Deployed AI Engineer do?

Can he help with LLM fine-tuning or MCP integration?

Let's talk about your next build.