Charbel Dandjinou
AI R&D Engineer - MLOps Tech Lead / Principal GenAI Developer
Lyon, France
French (Native) • English (C1/Advanced) • Gungbe (Native) • Japanese (Beginner) • Fon (Native) • Yoruba (Advanced) • Ewe (Advanced)
Professional Summary
Deep tech builder with expertise in domain-specific generative AI, autonomous infrastructure deployment, and strong theoretical background. Active AI evangelist, educator, team leader, and research contributor. Self-learner reading ~2 AI papers daily. Innovative thinker who solves problems in original ways and invents new methods to tackle complex challenges.
Professional Experience
Currently holding two concurrent leadership positions:
Generative AI Programme Lead / Principal Developer
Oct 2024 - PresentExxact Robotics / EXEL Industries Group
- Lead 3 RAG programs (industrial, HR, legal); judge-guided RAG reaching near-perfect legal-QA relevance on 3k+ queries (statistically significant vs baseline)
- Multimodal RAG: ColPali-style late interaction for layout/tables/images + text; hybrid dense+BM25; adaptive chunking; LangChain/LangGraph orchestration
- Training: QLora + RLHF (DPO/GRPO) for domain Q&A; embedding fine-tuning (contrastive, hard negatives); cross-encoder reranking
- Serving: vLLM/Ollama, KV cache, PagedAttention, quantization (AWQ/GPTQ/GGUF) → 2-3× throughput on A100
- Reliability: MRR/MMR, ablations, significance testing; sovereign deployments (no external APIs)
- Delivered 15+ internal/external GenAI talks and workshops to 200+ attendees
MLOps Tech Lead
Aug 2024 - PresentExxact Robotics / EXEL Industries Group
- Own company-wide AI infra: Kubernetes (on-premise), GitOps (ArgoCD), observability (Prometheus/Grafana/Loki), MLflow
- Standardize packaging, datasets/artifacts, reproducible deployments; mentor DevOps and AI apprentice
- Define SLOs for latency/GPU; implement data/feature drift monitoring in production
- Ensure AI security, compliance, and data sovereignty for enterprise deployments
Solo MLOps Engineer
Mar 2024 - Jul 2024Exxact Robotics / EXEL Industries Group
- Created and executed company-wide MLOps roadmap from scratch
- Built full MLOps stack: MLflow server, dataset versioning, artifact store, benchmark tools
- Implemented Infrastructure as Code (IaC) using Terraform with GitOps practices (ArgoCD)
- Set up on-premise GPU Kubernetes cluster with complete observability stack
- Delivered entire AI infrastructure single-handedly with 100% cost control vs cloud
AI Research & MLOps Engineer
Sep 2023 - Feb 2024Exxact Robotics / EXEL Industries Group
- Trained segmentation models for crop and weed detection
- Built Optuna-based tool for augmentation strategy search using Bayesian optimization
- Researched conformal prediction for active learning
- Delivered production-ready reproducible pipeline
AI Research Engineer + MLOps Onboarding
Jun 2023 - Sep 2023Exxact Robotics / EXEL Industries Group
- Transitioned to MLOps while maintaining research responsibilities
- Set up MLflow experiment tracking infrastructure
- Deployed first MLOps PoC using cloud infrastructure
- Technologies: ZenML, MLflow, Kubernetes (GKE), MinIO, GCP bucket
AI Research Engineer (Apprenticeship)
Oct 2022 - Jun 2023Exxact Robotics / EXEL Industries Group
- Designed PowerBALD-based active learning pipeline for semantic segmentation with WUR
- Developed RL-based data augmentation search using Bayesian optimization
- Created custom augmentation tool based on Optuna for hyperparameter tuning
- Achievement: Reduced annotation costs by 30%
- Co-authored paper presented at ICCV CVPPA 2023
Freelance AI Developer - Computer Vision Consultant
2020 - 2021Remote
- Designed and implemented object detection systems for diverse applications
- Retail theft detection: Real-time monitoring and alert systems
- Agricultural anomaly detection: Crop disease and pest identification
- Delivered end-to-end computer vision solutions to multiple clients
- Helped businesses automate surveillance and quality control processes
AI Research Intern - Computer Vision
Jun 2019 - Sep 2019Laboratoire PRISME, Orléans
- Master 2 research internship on deep learning for embedded systems
- Achieved +70% accuracy improvement over classical computer vision methods
- Optimized neural networks for deployment on low-power Linux boards
- Built Qt-based demonstration GUI for industry partners (LIFAT + LENZI)
- Research Stack: C++, Qt, TensorFlow, OpenCV, model optimization
Full-Stack Developer (Intern)
May 2018 - Nov 2018Fonddeuzz
- Improved web portal UX
- Prototyped deep-learning recommendation engine
- Delivered first working recommender demo to founders
- Technologies: HTML/CSS/JS, Node.js, React, TensorFlow-JS
Auxiliaire de vacances
Feb 2020BNP Paribas, Pantin
- Admin & archiving on ALIS platform
Technical Skills
Model Training & Optimization
Advanced PyTorch (DDP/FSDP), mixed precision (AMP/BF16/FP16), custom training loops
Augmentation strategy & HPO (Optuna), regularization, early-stopping, TTA
Data/feature drift detection & monitoring
Evaluation: IoU, mAP, PR, MRR/MMR, ablations, significance testing
Deep Learning & AI/ML
PyTorch, TensorFlow, Hugging Face Transformers
Active Learning: Baal, PowerBALD
Optimization: Optuna, Bayesian optimization
Computer Vision: OpenCV, semantic segmentation, object detection
Methods: Conformal prediction, RL-based data augmentation
Generative AI & LLM Operations
Fine-tuning: QLora/LoRA, RLHF (DPO/GRPO) for domain Q&A; embedding fine-tuning (contrastive, hard negatives)
Retrieval: Dense bi-encoders (FAISS-GPU, ChromaDB), cross-encoder reranking, layout-aware pipelines (ColPali)
RAG Methods: Hybrid dense+BM25, adaptive chunking, query reformulation; LangChain/LangGraph orchestration
LLM Serving: vLLM, Ollama, SGLang; KV cache, PagedAttention; quantization (AWQ/GPTQ/GGUF)
Agents: Smol Agent, MCP (Model Context Protocol)
MLOps & Infrastructure
Orchestration: Kubernetes (GKE & on-premise), Docker, Helm
IaC: Terraform, Ansible
CI/CD: ArgoCD (GitOps), GitHub Actions
ML Platforms: MLflow, ZenML
Storage: MinIO, GCS, Ceph, NFS
Web Development & Design
Frontend: React, Vue.js, Next.js, Tailwind CSS, Canvas API
Backend: Node.js, Express, RESTful APIs, GraphQL
UI/UX: Complete design process, Figma, Adobe Creative Suite
Creative Coding: Three.js, D3.js, real-time visualizations
Visual AI & Creative Tech
Diffusion Models: Stable Diffusion, FLUX, Midjourney
Generative Models: Autoregressive models (GPT-style), VAE, GAN architectures
Fine-tuning: LoRA, DreamBooth, Textual Inversion, Hypernetworks
Control: ControlNet, IP-Adapter, T2I-Adapter, Pose guidance
Workflows: ComfyUI advanced pipelines, A1111, InvokeAI
Applications: Product design, concept art, fashion tech
Monitoring & Observability
Stack: Grafana, Prometheus, Loki
Custom: Structured logging, metrics collection, GPU monitoring
Embodied AI & Robotics
NeuroGraph: Long-horizon memory (vector retrieval + dynamic knowledge graphs with temporal decay)
VLA Models: VLM/VLA integration, memory-conditioned control
Agentic Physical AI: LLM-robot tool use (MCP), safety gates
Frameworks: LeRobot (Hugging Face), ACT, Diffusion Policy
Platforms: ROS2 Humble, Isaac Sim; sim-to-real transfer
Research Contributions & Publications
- "Novel Hybrid RAG Architecture for Domain-Specific Question Answering" (2024) - Achieved significant MRR increase
- "Conformal Prediction for Active Learning in Agricultural AI" (2024)
- "Cloud-to-On-Premise Migration Strategies for AI Infrastructure" (2024)
Research Metrics
• 730+ AI papers analyzed (~2/day continuous learning)
• 5+ novel algorithms developed and deployed to production
• 30-99% improvement metrics across all research projects
• 4+ researchers/engineers mentored
Key Achievements
Near-perfect relevance on internal legal-QA with judge-guided RAG (3k+ queries; statistically significant vs baseline)
≈30% cost reduction labeling cost via PowerBALD active learning (CVPPA @ ICCV 2023)
>70% accuracy gain replacing classical CV with YOLOv3 (2019, PRISME)
On-prem GPU cluster ML platform built from scratch; improved latency and cost vs cloud
Invited Speaker GOSIM 2025; ICCV workshop 2023 and arXiv 2024; reviewer (ECCV 2024 workshop)
200+ attendees at 15+ GenAI presentations as AI evangelist
Founded IROKO international NGO bridging AI innovation between Europe and Africa
Created CD_IA website with real-time fractal animations and dual-theme design
Featured Talk
GOSIM 2025 - Context Engineering for AI Applications & Agents
Invited keynote presentation on advanced context engineering techniques for LLM applications and agentic systems. Covered judge-guided RAG architectures, multimodal retrieval strategies, and production deployment best practices for sovereign AI systems.
Leadership & Community Initiatives
IROKO Association
Founder & President • Feb 2025 - Present
- Founded international NGO supporting emerging-market talent worldwide (primary focus: Africa)
- Mission: Democratizing AI knowledge and fostering innovation in underserved communities
- Organize AI seminars and "AI Afterwork" networking events connecting global talent
- Build bridges between developed and emerging AI ecosystems
- Develop partnerships with universities and tech hubs internationally
- Impact: Creating pathways for underrepresented talent in global AI research
Deep Takka (IROKO Research Lab)
Head of AI Research • May 2025 - Present
- Launched research lab as IROKO's technical innovation arm
- Leading Project Genesis: foundational research initiatives
- Focus: Culturally-aware AI, low-resource languages, edge AI optimization
- Building research team and establishing international collaborations
- Status: Multiple research projects in development phase
Academic Mentoring & Supervision
Current Supervision
Master's Apprentice - GenAI Research Assistant (2024-Present)
- Direct supervisor and mentor for Master 2 AI student
- Research: Multimodal RAG systems, evaluation frameworks
- Impact: Accelerated GenAI project delivery by 40%
Past Supervision
Robotics Learning Research Intern (2024)
- Led hiring process and supervised research
- Topic: NVIDIA Eureka framework for robotic task learning
- Successfully integrated findings into production pipeline
Neural Architecture Search Research Intern (2023)
- Co-supervised research on automated model optimization
- Focus: NAS for resource-constrained edge deployment
Side Projects & Community
Creative & Technical Projects
- Personal Website (CD_IA): Designed and developed dual-theme portfolio with real-time fractal visualizations (Julia sets, Sierpinski triangles, glitch patterns) using vanilla JavaScript and Canvas API
- Generative AI Artist: Creating product designs and concept art using custom-trained diffusion models
- Robot Learning: Building hobby projects with ACT, VLM/VLA models, and Diffusion Policy
- LeRobot Contributor: Active experimentation with Hugging Face's robot learning framework
Community Engagement
- Hackathon Mentor: Mentored participants at LeRobot Hackathon
- AI Fairness: Developing inclusion datasets for minority cultural items
- Object Recognition: Fashion-tech applications for global textiles and patterns
- Education: AI education initiatives in emerging countries
- Open Source: Contributing to LeRobot, Hugging Face ecosystem, and community projects
Education
Master 2 Artificial Intelligence & Management
IA School, Paris • 2022-2023 •
Master 1/2 Computer Science (DataScale)
Université Paris-Saclay • 2019-2021 •
Master Systems & Networks
IFRI-UAC, Benin • 2017-2019 • C
Additional Information
Security Clearance: Experience with sovereign AI systems (no external APIs)
Compliance: AI security and compliance management
Languages: Fluent in technical English for paper reviews and conferences
Availability: Full-time position
Location Preference: Open to discussion