MeetAlexis Balayre
Who am I?
Name: Alexis Balayre
Birth Date: Avril 15, 2001
Nationality: French
Location: Paris, France
Degrees: ISEP Software Engineering Master Degree | Msc in applied AI at Cranfield University
Specialisations: Data Science | Machine Learning | Software Engineering
Role: AI Engineer
AI Engineer with a dual background in Software Engineering and Data Science, experienced in delivering production-ready AI solutions that bridge research and business impact. Skilled in Machine Learning, Generative AI, and Agentic Systems, with a proven ability to turn prototypes into scalable products that create measurable value. Recognised for resourcefulness, determination, and meticulous attention to detail, and driven by a strong interest in AI Safety.
Education
Cranfield University - MSc in Computational and Software Techniques in Engineering
Sept. 2023 - Sept. 2024MSc at Cranfield University as part of a double degree programme with ISEP.
Cranfield University, located in the UK, is a distinguished public institution exclusively dedicated to postgraduate education and research. It boasts a specialisation in science, engineering, technology, and management, holding the unique distinction of being the UK's sole postgraduate-only university.
Modules studied:
- Machine Learning and Big Data
- Artificial Intelligence
- High Performance Technical Computing
- Cloud Computing
- Small-Scale Parallel Programming
- Management for Technology
ISEP - Engineering Master Degree
2021 - 2024Engineering cycle at ISEP in Paris. Specialisation in Data Intelligence.
ISEP is a French digital engineering school located in Paris. It trains general engineers in the key fields of digital technology: IT & Cybersecurity - Electronics & Robotics - Telecommunications & Internet of Things - Imaging - Artificial Intelligence.
CVUT - Academic Semester Abroad
Feb. 2021 - Jun. 2021Academic semester in English at the Csech Technical University in Prague.
Modules studied:
- Telecommunication Systems and Networks
- Introduction to Cyber Security
- Environmental Engineering
- Discrete mathematics
- Programming
- EnglishISEP - International Integrated Cycle (CII)
2019 - 2021Preparatory years at the ISEP engineering school in Paris.
The CII follows a programme specific to ISEP, balanced across three teaching areas: Fundamental Digital Sciences | Techniques & Technologies | Languages, Cultures, Humanities and Sustainable Development. It includes an international semester from the second year.
Experiences
AI Engineer at Acolad
Sept. 2025 - PresentAcolad, represented by its flagship brands Acolad, TextMaster, and Ubiqus, is a global leader in language and content solutions with a presence in 25 countries and a network of more than 2,500 internal experts and 20,000 external linguists. As an AI Engineer, I contribute to the development and launch of next-generation AI interpreting solutions, transforming ideas into market-ready products and advancing Acolad’s mission of seamless multilingual communication.
- Harness Generative AI, Agentic Systems, and advanced speech technologies to design real-time multilingual communication solutions.
- Build and optimise LLM-native applications and vector-driven retrieval pipelines to enable scalable and intelligent language experiences.
- Industrialise experimental models into production-ready applications through MLOps best practices, cloud architectures, and rapid iteration with product teams.
Data Scientist at Dassault Systèmes
Jan. 2025 - Jul. 2025Dassault Systèmes, the 3DEXPERIENCE Company, empowers businesses and individuals with virtual universes to foster sustainable innovation. As a Data Scientist, I worked in the Industry Market Intelligence - Corporate Strategic Planning team to automate and optimise data processes, ultimately driving strategic insights and enabling informed decision-making.
- Accelerated strategic reporting and Market Intelligence by automating data workflows and analysing large-scale datasets (millions of records) using Python and SQL.
- Designed and implemented data-driven solutions leveraging Web Scraping, Natural Language Processing (topic modeling, sentiment analysis), and Generative AI (LLM, RAG, GraphRAG) to extract insights from both structured and unstructured data.
- Built and maintained Competitive Intelligence and monitoring tools to support executive decision-making and strengthen Dassault Systèmes' positioning in its Business sectors.
Data Engineer Freelance at Sidetrade
Oct. 2024 - Nov. 2024Sidetrade is a leading AI-powered SaaS platform that helps companies enhance working capital and cash flow performance by optimising customer relationship management and automating financial processes.
- Defined the architecture and data workflows for an automated carbon footprint reporting solution, aimed at reducing manual work and improving reporting speed.
- Designed the integration of data from NetSuite, Egencia, Eurécia, and Navan into Power BI to enable dynamic, real-time dashboards with exportable insights.
- Proposed an ETL solution using Microsoft Fabric to streamline the processing of both structured and unstructured data.
- Project was discontinued during implementation due to data privacy constraints related to GDPR compliance.Research Student at Cranfield University
May 2024 - Sept. 2024Master's Thesis in collaboration with Airbus, supported by UK Research and Innovation (UKRI) and the Aerospace Technology Institute (ATI), focused on enhancing the efficiency and accuracy of automated ground refueling systems for Smart Airports. Developed an advanced machine learning framework combining the object detection model YOLOv10 and a proposed deep learning sequence model (SizPos-GRU) to accurately predict the future position of commercial aircraft's refueling port in a video stream.
ETHGlobal ETHOnline 2023 Winner
Oct. 2023ETHOnline is a three week long online hackathon with over $200,000 USD in prizes as well as a series of curated summits, celebrating some of the most significant happenings & learnings from the past 12 months in web3. Enigma introduces the Secret NFTs standard: a unique dual URI approach. Each NFT showcases a public and a private layer. Only owners have full access. From art to memberships, prioritizing privacy in the digital domain is paramount. Enigma won 2 prizes at the 2023 ETHGlobal ETHOnline hackathon : "The Graph — Best New Subgraph or Substream" and "Scroll — Pool Prize".
Vice President of the Blockchain Lab at Garage ISEP
Sept. 2022 - Sept. 2023Garage ISEP is the student association of ISEP dedicated to technology (Blockchain, Artificial Intelligence, ...). Organisation of workshops and conferences to learn and master Blockchain technologies.
Blockchain Developer at CoinShares
Sept. 2022 - Jan. 2023CoinShares is Europe's largest and oldest crypto asset investment company, managing billions of dollars in assets. Discovery of Decentralised Finance within the DeFi team and realisation of missions to build a decentralised asset management tool.
Chainlink Spring 2022 Winner
May 2022Hackathon to build the next generation of Web3 apps with $500K+ in prizes. Winner of Chainlink Top Quality Projects.
ETHGlobal HackMoney 2022 Winner
May 2022World's largest DeFi hackathon. Sleepn is a decentralised sleep tracking application that allows you to earn money by sleeping. Sleepn won 2 prizes at the 2022 ETHGlobal HackMoney hackathon : "Polygon — Best App" and "Superfluid — Best Use With Another Partner".
Finalist in Devoteam's Cyber Hackthon
Oct. 2021 - Nov. 2021Finalist in the 'Devogame' cybersecurity competition organised by Devoteam out of more than 3,800 entrants. Proposed a system for verifying a company's logs using a private blockchain and a consensus system based on private keys.
Skills
Programming Languages
Python
JavaScript
TypeScript
Solidity
SQL
Java
C/C++
Rust
Shell / Bash
AI & Data Intelligence
PyTorch Lightning
TensorFlow
Scikit-learn
NumPy
pandas
Polars
Matplotlib
Seaborn
Plotly
OpenCV
spaCy
NLTK
XGBoost / LightGBM
MLflow
Hugging Face Transformers
LangChain
LangGraph
LlamaIndex
vLLM
Ollama
Databases
MongoDB
MySQL
PostgreSQL
Cassandra
Timestream
InfluxDB
Neo4j
Redis
Elasticsearch
Milvus
Chroma
Data Engineering Tools
Apache Airflow
Apache Spark
Apache Kafka
Frontend
Next.js
React.js
Vue.js / Nuxt
TailwindCSS
HTML / CSS
React Native
Streamlit
Gradio
Backend
Node.js / NestJS
FastAPI
Flask
Django
Hosting & Cloud Services
Netlify
Digital Ocean
Vercel
RunPod
Cloudflare
AWS
Azure
Server Management & DevOps
Docker
Git / GitHub Actions / CI/CD
Linux (Ubuntu, CentOS)
Kubernetes
NGINX
Other Tools
VSCode
Power BI
Tableau
LaTeX
Markdown
Projects
AuraHelpeskGraph: GraphRAG Support Chatbot
A support chatbot that leverages local LLMs, vector similarity search, and knowledge graphs to provide contextual assistance by finding and presenting solutions from historical support tickets.
RagDocs: RAG-Powered Chatbot for Technical Documentation
RagDocs is a cutting-edge open-source solution that revolutionizes how you interact with documentation. By combining the power of local LLMs with state-of-the-art Retrieval-Augmented Generation (RAG), developers can instantly get accurate answers from their documentation without any API costs. Say goodbye to expensive API calls and privacy concerns. With RagDocs, all your documentation stays private while providing ChatGPT-like interactions. Built with Milvus vector search and Next.js, it's production-ready and easy to deploy. Experience the future of documentation search with complete data privacy and no usage fees.
Master's Thesis: Future Position Prediction for Pressure Refuelling Port of Commercial Aircraft:
This thesis develops a deep learning framework to predict the future position of aircraft refuelling ports, enhancing automated refuelling systems. The approach integrates a fine-tuned YOLOv10 model for detection with the proposed 'SizPos-GRU' sequence model, which captures temporal and spatial relationships from video frames using an encoder-attention-decoder architecture. Results show that the SizPos-GRU model outperforms other models, achieving an Average Displacement Error (ADE) of 4.28% and a Final Displacement Error (FDE) of 9.18% when using 30 past frames to predict 60 future frames. For predictions using 15 past frames to predict 30 future frames, the model achieved an ADE of 2.15% and an FDE of 4.83%. These results demonstrate significant improvements in prediction accuracy, proving the framework’s effectiveness in automating and enhancing aircraft refuelling operation.
GPTAggregator
GPTAggregator is a Python-based application that provides a unified interface for interacting with various large language models (LLMs) via their respective APIs. The project is designed to be user-friendly and easily extensible, making it a powerful tool for developers, researchers and anyone interested in exploiting the capabilities of large language models. GPTAggregator makes it possible to switch seamlessly from one model to another within the same conversation, centralise conversation storage, automatically optimise messages, and much more.
AI-Powered Meeting Summarizer
The AI-Powered Meeting Summarizer is a Gradio-powered application that converts audio recordings of meetings into transcripts and provides concise summaries using whisper.cpp for audio-to-text conversion and Ollama for text summarization. This tool is ideal for quickly extracting key points, decisions, and action items from meetings.
Group Project: Deep Learning for Turbulence Modelling
This project focuses on the innovative integration of machine learning with computational fluid dynamics (CFD) to address the limitations of traditional turbulence models. By incorporating Physically Informed Neural Networks (PINNs) and employing the Sparse Identification of Nonlinear Dynamical Systems (PySINDy) approach, we aim to improve the accuracy and efficiency of turbulent flow simulations. This interdisciplinary effort aims to harness the power of high-performance computing to revolutionise the predictive modelling of fluid dynamics.
Chest X-Ray Abnormalities Detection with Faster R-CNN
This project leverages the Faster R-CNN model with a ResNet-50 backbone, implemented using PyTorch Lightning, for the detection and localisation of thoracic abnormalities in chest X-ray images.
COVID-19 Data Analysis Project Using Apache Spark
This project harnesses Big Data and Machine Learning technologies to analyse the global impact of the COVID-19 pandemic. Utilising Apache Spark, it processes extensive datasets of COVID-19 cases, uncovering insights into the virus's spread and effects.
Cloud Computing and IoT for Environmental Monitoring Project
This project integrates Cloud Computing with the Internet of Things (IoT) for comprehensive environmental monitoring, with a focus on air quality analysis. Utilising Apache Spark and Amazon Timestream, it manages large volumes of data from IoT sensors to calculate the Air Quality Index (AQI) accurately, offering insights into environmental conditions.
PriceSense: Correlating News Sentiment with Stock Prices
This project examines the relationship between financial news sentiment and stock market prices using two data pipelines. The first pipeline uses LocalStack to mimic Amazon S3 for data storage and messaging, while the second utilises Apache Kafka for real-time streaming and message exchange. Both pipelines process financial news and stock price data, calculate sentiment scores, merge this data, and then index it into Elasticsearch for analysis and visualisation.