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MP DATA

MP DATA

www.mpdata.fr

3 Jobs

141 Employees

About the Company

MP DATA est une société de Conseil spécialisée dans la transformation digitale des entreprises. Plus particulièrement en Data Science et Recherche Opérationnelle

Listed Jobs

Company background Company brand
Company Name
MP DATA
Job Title
Data Architect – AI Agents & Data Platforms (H/F)
Job Description
Job Title: Data Architect – AI Agents & Data Platforms Role Summary: Design and implement end‑to‑end data and AI solutions for enterprise clients, focusing on modern data platforms, MLOps/LLMOps, and multi‑agent architectures. Collaborate with technical leaders to deliver scalable, cloud‑native infrastructures that support advanced AI capabilities such as RAG and generative models. Expectations: - 5+ years of experience in data engineering, data architecture, or data platform roles. - Proven track record of designing modern data architectures (lakehouse, data lake, data warehouse). - Senior‑level understanding of large‑scale cloud deployments, MLOps/LLMOps, and multi‑agent systems. Key Responsibilities: - Architect end‑to‑end AI agent infrastructures and multi‑agent systems tailored to client needs. - Design large‑scale Retrieval‑Augmented Generation (RAG) solutions and LLM‑based pipelines. - Build and refine modern data platforms (lakehouse, lake, warehouse) using industry‑standard tools. - Define MLOps and LLMOps pipelines and integrate them into continuous delivery workflows. - Conduct technical scoping, architecture reviews, and technical guidance for project teams. - Engage with client CTOs/Chief Data Officers to align technical solutions with business objectives. Required Skills: - Cloud proficiency (AWS, GCP, Azure). - Hands‑on experience with Databricks, Snowflake, BigQuery, or equivalent data platform technologies. - Strong knowledge of data pipeline design, distributed computing, and performance tuning. - Deep understanding of LLM, RAG, and AI agent principles and their operationalization. - Ability to synthesize complex technical requirements and communicate them to non‑technical stakeholders. Required Education & Certifications: - Diploma from an engineering school or a Master’s degree in Computer Science, Information Technology, Data Science, or Artificial Intelligence. ---
Boulogne-billancourt, France
Hybrid
Mid level
13-03-2026
Company background Company brand
Company Name
MP DATA
Job Title
ML Engineer - GenAI / LLM (Aéronautique) Junior
Job Description
Job title: ML Engineer – GenAI / LLM (Junior) Role summary: Design, build, and operate generative AI solutions for the aerospace sector, focusing on Retrieval Augmented Generation (RAG) pipelines, domain‑specific conversational agents, and integration with maintenance management systems. Expectations: • Independent, proactive engineer with strong synthesis skills. • Ability to translate business requirements into technical solutions. • Deliver production‑grade code within short cycles. • Maintain end‑to‑end MLOps pipeline, monitor drift, cost, and latency. Key responsibilities: - Gather requirements with business stakeholders and translate them into AI solution specifications. - Design and implement RAG pipelines that ingest technical manuals and maintenance documentation. - Develop conversational agents tailored to maintenance operations and integrate them into CMMS tools. - Deploy models on GCP (Vertex AI, BigQuery, Cloud Functions) and manage infrastructure with Terraform. - Monitor deployed solutions for model drift, performance, and cost; adjust as needed. - Collaborate with data engineering and MLOps teams to ensure scalable, secure delivery. Required skills: - Strong foundation in machine learning concepts (model training, evaluation, fine‑tuning). - Proficient in Python, familiar with libraries such as PyTorch/TensorFlow, LangChain, or similar. - Experience with GCP services: Vertex AI, BigQuery, Cloud Storage, Cloud Functions. - Familiarity with Terraform for IaC and GCP resource management. - Knowledge of RAG architectures, document ingestion, embedding generation, and retrieval mechanisms. - Ability to develop conversational agents (chatbot frameworks, dialogue management). - Understanding of MLOps practices: model versioning, CI/CD, monitoring, and alerting. - Excellent written and verbal communication, with ability to explain technical concepts to non‑technical stakeholders. - Self‑motivated, independent, and proactive in troubleshooting and optimization. Required education & certifications: - Graduate of a Grande École or equivalent engineering/technological university with a degree in Computer Science, Data Engineering, Artificial Intelligence, or related field. - Optional: Google Cloud or AI‑specific certifications (e.g., GCP Professional Data Engineer, Vertex AI, or ML Engineer) are a plus.
Boulogne-billancourt, France
Hybrid
Junior
13-03-2026
Company background Company brand
Company Name
MP DATA
Job Title
Data Scientist - Machine Learning / Time series (Energie) - Junior/Confirmé
Job Description
Job title: Data Scientist – Machine Learning / Time Series (Energy) – Junior/Confirmed Role Summary Develop and enhance predictive models for solar and wind energy production using meteorological data. Build a reusable library to streamline model development. Collaborate with industrial clients to translate data insights into production forecasts. Expectations - Apply advanced machine learning techniques (Random Forest, XGBoost). - Design, train, and evaluate deep learning models, addressing issues such as vanishing gradients and overfitting. - Analyse time‑series data, assessing stationarity, decomposition, and correlation. - Containerize solutions with Docker, create and deploy images, debug containers. - Deploy models on AWS SageMaker, integrating MLflow tracking. - Produce clear documentation and propose process improvements. Key Responsibilities 1. Build and refine predictive models for solar and wind output based on weather inputs. 2. Develop a standard library for model development, including preprocessing, feature engineering, and evaluation pipelines. 3. Deploy models to production environments using Docker and AWS SageMaker. 4. Manage model versioning and experiment tracking with MLflow. 5. Communicate results to stakeholders, translating complex analyses into actionable insights. 6. Identify opportunities to optimize data pipelines and modeling workflows. Required Skills - Proficiency in machine learning algorithms (Random Forest, XGBoost). - Experience with deep learning frameworks, model training, interpretation, and debugging. - Strong grasp of time–series concepts: stationarity, decomposition, correlation. - Competence in Docker containerization (image construction, deployment, debugging). - Familiarity with AWS SageMaker and MLflow. - Knowledge of meteorological datasets and how to integrate them into predictive models. - Excellent analytical thinking, autonomy, and ability to propose improvements. Required Education & Certifications - Graduate engineering degree (Grande École or equivalent) in computer science, data science, statistics, or related field. - Certifications in AWS services (e.g., SageMaker) or machine learning are advantageous.
Boulogne-billancourt, France
Hybrid
Junior
18-03-2026