ANASS SMALI

AI Engineer

https://talent.gravityer.com/anass-smali

AI Engineer with less than a year in Machine Learning, LLMs & MLOps Systems

Key Strengths

Strong foundational knowledge in AI/ML, NLP, and Computer Vision, directly aligning with an AI Engineer role.
Demonstrated experience in MLOps, including deployment, monitoring, and observability on GCP, which is critical for production AI systems.
Hands-on experience with advanced AI concepts like Retrieval-Augmented Generation (RAG), multi-agent systems (Agentic AI), and LLM fine-tuning.
Proficiency in key AI/ML frameworks and tools such as LangChain, LangGraph, TensorFlow, PyTorch, Docker, Kubernetes, and Terraform.
Proven ability to deliver business impact through AI solutions, evidenced by quantifiable results in projects (e.g., F1-Weighted score, reduction in search time, early fault detection).

Cultural & Operational Fit

Cultural Fit Analysis

The candidate's project diversity, ranging from NLP classification to RAG chatbots and predictive maintenance, indicates adaptability and a broad interest in AI applications. Their involvement in both academic R&D and industry internships (Orange Business Services, SEW USOCOME) suggests a practical, application-oriented approach. The mention of 'Open Source' as an interest aligns with collaborative and knowledge-sharing cultures. The candidate's profile shows a strong alignment with a dynamic, innovation-driven environment typical for an AI Engineer role.

Soft Skills & Operational Fit

The candidate demonstrates strong problem-solving skills, an analytical and results-oriented mindset, and the ability to work in international teams. Their experience with Agile/Scrum methodologies indicates good operational fit for modern development environments. The ability to communicate technical concepts effectively is also highlighted.

AI is analyzing your overall score…

Identifying your key strengths…

Evaluating your skill match against the job requirements…

Assessing your cultural and operational fit

About

Ingénieur Data & Intelligence Artificielle avec une expertise en Machine Learning, LLMs, MLOps et systèmes IA en production. Expérience sur des projets industriels internationaux couvrant l'ensemble du cycle de vie IA: collecte de données, NLP, Computer Vision, entraînement de modèles, déploiement cloud et monitoring. Capable de transformer des problématiques métier complexes en solutions IA robustes, scalables et orientées impact business.

Top Skills

Machine LearningLlmsMlopsComputer Vision

Skills

Machine LearningLlmsMlopsNlpComputer VisionSVMmlpGoogle Cloud PlatformVertex AiBigQueryCloud FunctionsDockerTerraformLookerLanggraphAgentic AiPythonLangchainOpenAI APIFastapiRest ApisRetrieval Augmented Generation (Rag)Milvusgpt-4DeepEvalKubernetesStreamlitinfluxdbOCRGPTmistralMongoDBRJavaC++C++supervised-learningDeep LearningAnomaly DetectionClusteringPrompt EngineeringEmbeddingsmulti-agent-systemsTool-callingAi WorkflowsScikit LearnPyTorchKerashuggingfaceOpencvAWSMlflowAirflowPower BITableauLooker StudioMatplotlibPlotlyTestingCiCdversioningDistributed Systems

Education

Université de Strasbourg

Master Sciences des Données et Systèmes Complexes · Data Science

August 1, 2024 – June 30, 2026

Télécom Physique Strasbourg

Diplôme d'Ingénieur Informatique & Réseaux · Data Science & IA

August 1, 2023 – June 30, 2026

Lycée Mohamed V

Classes Préparatoires MP

August 1, 2021 – June 30, 2023

Experience

Orange Business Services

AI/ML Engineer | NLP, GenAl & Production Al Systems

March 1, 2026 – August 1, 2026

Paris, Île-de-France, France

SEW USOCOME

AI Engineer | RAG & Predictive Maintenance

June 1, 2025 – August 1, 2025

Strasbourg, Grand Est, France

Télécom Physique Strasbourg

Projet R&D Computer Vision & NLP

January 1, 2025 – Present

Strasbourg, Grand Est, France

Projects

Agentic AI System - Multi-Agent LLM Assistant

January 1, 2026 – June 1, 2026

• Développement d'un système d'agents IA multi-tâches basé sur LangGraph et architectures Agentic AI pour l'automatisation de tâches complexes. • Implémentation d'un mécanisme de LLM Routing permettant la sélection dynamique des outils et workflows selon l'intention utilisateur. • Intégration d'une mémoire conversationnelle persistante pour le suivi de contexte et l'exécution d'actions multi-étapes. • Développement de capacités autonomes : création et lecture de fichiers, résumé de documents, recherche web via DuckDuckGo, gestion d'emails, accès calendrier et météo via APIs externes. • Connexion à plusieurs MCP Servers (Model Context Protocol) afin d'étendre dynamiquement les capacités des agents IA. • Orchestration de workflows IA avec tool-calling, gestion d'état, raisonnement multi-étapes et exécution conditionnelle.

Key Strengths

Strong foundational knowledge in AI/ML, NLP, and Computer Vision, directly aligning with an AI Engineer role.
Demonstrated experience in MLOps, including deployment, monitoring, and observability on GCP, which is critical for production AI systems.
Hands-on experience with advanced AI concepts like Retrieval-Augmented Generation (RAG), multi-agent systems (Agentic AI), and LLM fine-tuning.
Proficiency in key AI/ML frameworks and tools such as LangChain, LangGraph, TensorFlow, PyTorch, Docker, Kubernetes, and Terraform.
Proven ability to deliver business impact through AI solutions, evidenced by quantifiable results in projects (e.g., F1-Weighted score, reduction in search time, early fault detection).

Cultural & Operational Fit

Cultural Fit Analysis

Soft Skills & Operational Fit