Marc Pinet

AI Researcher

Grenoble, Auvergne-Rhône-Alpes, France0 mo experience

AI EnabledAI ML Practitioner

Key Highlights

Expert in anomaly detection and machine learning.
Strong background in self-supervised learning techniques.
Proven track record in developing AI solutions for telecommunications.

Stackforce AI infers this person is a Machine Learning Specialist with a focus on Anomaly Detection in Telecommunications and IoT.

Contact

Skills

Core Skills

Anomaly DetectionMachine LearningInternet Of Things (iot)Frontend Development

Other Skills

Deep LearningSelf-supervised LearningTime Series AnalysisExplainable AILarge Language Models (LLM)Retrieval-Augmented Generation (RAG)GraphRAGLinear AlgebraStatisticsProbabilityPython (Programming Language)PyTorchArtificial Intelligence (AI)Research DevelopmentIndustrial Research

About

I'm passionate about machine learning, mathematics, and more generally about research and science. My current research interests lie in detection and explanation of anomalies in time series.

Experience

0 mo

Total Experience

Average Tenure

Current Experience

Orange

PhD Researcher in Machine Learning

Nov 2025 – Present · 7 mos · Meylan, Auvergne-Rhône-Alpes, France · On-site

Working on self-supervised deep anomaly detection for large-scale network infrastructure
Researching end-to-end AI solutions for failure and attack detection across connected devices
Investigating LLM+RAG approaches for automated anomaly interpretation using business knowledge
Focusing on heterogeneous data challenges (logs, metrics, traces) from network devices
Collaborating with Orange Innovation research teams and operational units
Aiming to reduce customer service costs through intelligent anomaly characterization
As part of a CIFRE PhD (French doctorate co-funded by both the company and France itself)

Deep LearningAnomaly DetectionSelf-supervised LearningTime Series AnalysisExplainable AILarge Language Models (LLM)+12

Lig - grenoble informatics laboratory

Industrial PhD Student

Nov 2025 – Present · 7 mos · Saint-Martin-d’Hères, Auvergne-Rhône-Alpes, France · On-site

Research on self-supervised deep learning for time series anomaly detection and explanation
Exploring novel approaches in XAI (Explainable AI) for anomaly characterization
Research laboratory under the supervision of CNRS and Inria
Working towards publications in machine learning and data mining conferences
Participating in laboratory research activities and academic collaborations
Investigating theoretical foundations of self-supervised learning for temporal data
As part of a CIFRE PhD (French doctorate co-funded by both the company and France itself)

Deep LearningAnomaly DetectionTime Series AnalysisSelf-supervised LearningExplainable AILarge Language Models (LLM)+11

Sap

2 roles

AI/ML R&D Engineer

Promoted

Aug 2024 – Sep 2025 · 1 yr 1 mo · Mougins, Provence-Alpes-Côte d'Azur, France · On-site

Developed unsupervised anomaly detection and correlation across logs, metrics, and traces
Combined log pattern extraction with time-series correlation
Optimized real-time pipeline: reduced memory usage by 70%
Increased scalability by 3x, processing 10M+ events daily
Built RAG-enhanced AI agent based on LLMs for detailed anomaly reporting

Anomaly DetectionArtificial Intelligence (AI)Python (Programming Language)Time Series AnalysisMachine LearningIndustrial Research+1

Data Scientist

Apr 2024 – Aug 2024 · 4 mos · Mougins, Provence-Alpes-Côte d'Azur, France · On-site

Exploring AI solutions development for anomaly detection
Time series trends analysis using tools such as Prophet, SARIMA, STL, DTW, etc.
Finding correlation between signals to enhance the Root Cause Analysis
Real-time robust pipeline for live data retrieval from internal APIs with data preprocessing

Anomaly DetectionArtificial Intelligence (AI)Python (Programming Language)Data SciencePyTorchDeep Learning+2