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PhD in Graph Deep Learning | Senior ML Engineer | Agentic Systems & Cloud Engineering

Passionate about the convergence of neural networks, industrial research, and data engineering, I enjoy designing innovative and high-performance solutions. Currently Senior Data Scientist at Mindflow specializing in agentic systems, spanning academic research and production engineering. My background combines a PhD in Graph Machine Learning with expertise in cloud data engineering (Kafka, Spark, Scala). I value collaborative work, driven by curiosity and the resolution of complex industrial challenges.

Professional Experience

Senior Data Scientist | Mindflow

Apr 2023 - Present | Paris - Remote

  • Agentic Orchestration: Architected a custom agentic layer for a no-code cybersecurity platform, implementing long-term memory, context-aware reasoning, LLM Observability, and hallucination mitigation.
  • Adaptive Orchestration Engine: Engineered an adaptive engine utilizing RAG and tool calls for reliable execution across multiple providers (OpenAI, Bedrock, Gemini, Mistral, LiteLLM).
  • Mentorship & Support: Mentored a talented AI team and shared expertise company-wide on agentic systems, RAG, and search optimization. Supported CSEs and Solution Designers in technical implementation.
  • Drift Monitoring: Developed an LLM drift monitoring framework (multi-route scenarios, parallel tool usage). Optimized internal search performance via a robust evaluation suite (MRR, F1, and NDCG).
  • Business Impact: Scaled from €0 to €1.5M ARR since joining; delivered AI solutions for major accounts (Thales, LVMH, Auchan, Doctolib, Hermès, Cloudguard, Savencia, Fast Retailing, Heetch, etc.). Mindflow LinkedIn page.
  • Tech Stack: LiteLLM, Langchain, LangGraph, RAG, tool calls, Bedrock, GPT, Gemini, Claude, Mistral, AWS Cloud.

Data Scientist (PhD) & Cloud Data Engineer | Lectra

Sept 2017 - Apr 2023 | Bordeaux

  • PhD Research (2020-2023): Enhanced “sections planning” algorithm by developing graph-oriented heuristics (Attention-based Deep Learning on Graphs) to minimize material waste. Trained models on 100,000+ real nestings using Azure ML, exceeding human expert precision. Now a live web service for industrial customers.
  • Data Engineering (2017-2020): Designed and implemented large data pipelines (1000+ events/sec) for massive IoT fleet (Lectra cutters) using Kafka, Spark and Scala. CI/CD workflows on Kubernetes (Docker, Jenkins).
  • Impact: One of the first Data Engineers hired at Lectra, supporting company revenue growth from €350M to €500M+ within a 500-person R&D department. Lectra LinkedIn page.
  • Tech Stack: Python, Scala, PyTorch, GNN, Azure ML, Apache Kafka, Spark, Kubernetes, Docker, IoT.

Data Scientist - Consultant | 2B Softeam Data & AI

Nov 2016 - Sept 2017 | Bordeaux

  • Cdiscount: Developed counterfeit detection algorithms using NLP and Hadoop (Hive/Spark) to secure the marketplace. Collaborated with the legal team to ensure regulatory compliance.
  • Lectra: Architected clothing pattern recognition tools using Deep Vision and initiated new large-scale data processing pipelines.
  • Tech Stack: NLP, Computer Vision, Hadoop, Hive, Spark, Java, Scala.

Software Engineer (Freelance) | Independent

May 2013 - Aug 2021 | Bordeaux / Remote

  • Data Science: Implemented cloud-native analytics solutions using Python, AWS SageMaker and Google BigQuery for diverse industrial clients: Cibler, Cdiscount.
  • Full-Stack Development: Developed high-performance web/mobile apps using React, Canvas API, WebRTC and Haxe.
  • Game Development: Engineered 2D/3D games using Unity3D (C#) and LibGDX. Winner of the Intel Android Codefest 2013. Showcased my game during the Mobile World Congress (MWC) 2014 in Barcelona on the Intel booth.
  • Tech Stack: AWS, BigQuery, React, Unity3D, C#, Javascript, WebRTC.

Project Manager & Software Engineer | Cybertek

Mar 2014 - Nov 2016 | Bordeaux

  • Logistics & Marketplace: Integrated several marketplaces (Amazon, Fnac) and optimized logistics by automating shipping workflows using carrier APIs (UPS, Chronopost).
  • E-commerce Platform: Redesigned the platform with responsive design, fuzzy search, and SEO optimization, increasing store visibility and sales by 100%+.
  • Retention: Enhanced internal ERP/CRM and data-driven communication strategies to optimize customer retention.
  • Tech Stack: C#, SQL Server, .NET, ERP, CRM, SEO, Marketplace APIs.

Software Engineer | Nexeya

Oct 2012 - Apr 2013 | Bordeaux

  • Naval Defense: Developed LYNCEA, a multi-sensor data fusion platform for naval defense. Integrated data acquisition modules and co-developed the high-performance network layer. [Video]
  • Tech Stack: C++, Qt, Network Engineering, Embedded Systems.

Research Engineer | LaBRI

Oct 2011 - Sep 2012 | Bordeaux

  • Web Services: Created Java JEE web services for research sharing and developed cross-language APIs (C++, C#, Java) with a real-time web application.
  • Tech Stack: Java JEE, C++, C#, Javascript, Web Services.

PhD Researcher & Software Engineer | Foxstream

Sep 2009 - Aug 2011 | Lyon

  • Computer Vision: Object tracking and one-class classification algorithms for video surveillance. Developed video analysis software solutions using C++, Winforms, and MFC in Agile environment. Foxstream LinkedIn page.
  • Video Retrieval: Engineered network video stream retrieval (OpenCV, Winsockets) and remote usage features.
  • Tech Stack: C++, OpenCV, Winforms, MFC, Agile, Winsockets.

Research Internships

Research Intern | Inserm - SBRI

Jan 2009 - Sep 2009 | Lyon

  • Developed a robotic system capable of learning rules through demonstration (Bayesian statistics, Markov networks).
  • Tech Stack: C++, TCL, Bayesian Statistics, Robotic Platform.

Research Intern | Laboratoire EMC

Jan 2008 - Sep 2008 | Lyon

  • Simulated neural-astrocyte network interactions using mathematical models and Java/RK4 to study focal cortical epilepsy.
  • Tech Stack: Java, RK4, Computational Neuroscience.

Education

PhD in Computer Science & Applied Mathematics | University of Bordeaux

Oct 2019 - Dec 2022 | Bordeaux

Dissertation: Graph-oriented deep learning algorithms for 2D nesting efficiency estimation.

Master’s Degree in Cognitive Sciences | University of Lyon

2008 - 2009 | Lyon

Publications

  • C. Lallier, “Graph Neural Network Comparison for 2D-Nesting Efficiency Estimation.” Journal of Intelligent Manufacturing, Springer Nature, 2023. DOI: 10.1007/s10845-023-02084-6
  • C. Lallier, “RĂ©seaux profonds basĂ©s graphes pour la prĂ©diction d’efficience de placements 2D.” PhD Thesis, UniversitĂ© de Bordeaux, 2022. theses.fr/2022BORD0421
  • C. Lallier, A. Fournel, E. Reynaud, “A Neurons-Astrocyte Network Model: From Synaptic Boosting to Epilepsy.” NeuroComp’10, 2010. hal.science/hal-00553451

Skills & Interests

  • Core Expertise: Python, PyTorch, Graph Neural Networks (GNN), Agentic Systems, RAG, LLMOps, Scala, Apache Kafka, Spark, AWS, Azure, Kubernetes.
  • Personal Projects: Tech Blog (Data Science, AI, Shaders), GitHub, Google Scholar.
  • Languages: French (Native), English (Full Professional Proficiency).
  • Interests: Sports (Crossfit, Running 10k & Half-marathon, Surfing, Hiking), Video games.