DescriptionWe are seeking a highly analytical and detail-oriented intern to join our marketing department at Astrolab Group. In this role, you will assist in the execution of marketing analytics initiatives and contribute to the continuous optimization of our digital campaigns. You will work closely with our marketing team to track performance metrics, identify actionable insights, and refine strategies to maximize impact and engagement. This is an exceptional opportunity to gain hands-on experience in data-driven decision-making within a dynamic professional environment.RequirementsCurrently pursuing a Bachelor’s or Master’s degree in Marketing, Business Analytics, Data Science, or a related field.Proficiency in using data analysis tools such as Microsoft Excel, Google Analytics, or similar platforms.Strong understanding of key performance indicators (KPIs) and marketing metrics used in digital campaign evaluation.Excellent analytical capabilities with the ability to interpret complex data sets and translate them into actionable recommendations.Professional proficiency in English, demonstrating strong written and verbal communication skills.

We are looking for a Cloud & DevOps Intern to build the cloud-native environment that runs an existing enterprise knowledge platform powered by LLMs and RAG. The goal is to make the platform secure, scalable, reliable and cost-efficient in production.The project involves building a solution capable of:Defining a cloud architecture adapted to LLM applications (networking, storage, managed services).Provisioning all infrastructure as code with Terraform.Containerizing the services and deploying them on managed Kubernetes, with automated CI/CD pipelines.Securing the platform with IAM, secrets management, encryption, policy as code and private access to LLM APIs.Scaling and monitoring the platform, and producing a cloud cost optimization report.This internship provides hands-on experience in cloud architecture, Kubernetes, DevSecOps and LLMOps.Estimated duration: 6 months (Final-year internship, PFE)Technical SkillsHands-on experience with Azure or GCP (AWS is also welcome).Knowledge of Docker, Kubernetes and Terraform.Experience with CI/CD tools (GitHub Actions or Azure DevOps).Understanding of cloud IAM, networking and security.Bonus Skills (Not Required but Appreciated)Policy as code (OPA Gatekeeper, Kyverno).LLM API load balancing and fallback (LiteLLM).Basic understanding of LLM and RAG architectures.Tech StackCloud: Azure or GCP (AKS, GKE, EKS)Infrastructure as Code: TerraformContainers & CI/CD: Docker, Kubernetes, GitHub Actions or Azure DevOpsSecurity: IAM, Key Vault or Secrets Manager, OPA Gatekeeper or KyvernoAI services & monitoring: Azure OpenAI or Vertex AI, LiteLLM, Azure Monitor or Cloud Monitoring

We are looking for a DevOps & AIOps Intern to build an AI-assisted incident response platform that helps operations teams detect, understand and resolve production issues faster. The goal is to reduce time to resolution by combining observability data with LLM-based root-cause analysis and safe automation.The project involves building a solution capable of:Correlating logs, metrics and traces from production services in one place.Detecting incidents and grouping related alerts to reduce noise.Suggesting likely root causes with LLM agents, evaluated against past incidents.Running automated runbooks with human approval gates before any action.Measuring impact on detection time and time to resolution.This internship provides hands-on experience in observability, LLM agents and DevOps automation.Technical SkillsComfortable with Linux, containers (Docker) and scripting (Python or Bash).Basic knowledge of Kubernetes and CI/CD.Understanding of monitoring and logging concepts.Familiarity with REST APIs.Tech StackObservability: Prometheus, Grafana, OpenTelemetry, Loki or ELKPlatform: Docker, KubernetesAI: LLM APIs, LangChain or similar agent frameworksAutomation: Python, Ansible, GitHub ActionsTools: Git, PagerDuty or Opsgenie

We are looking for a Robotics & Computer Vision Intern to build a vision-guided pick-and-place system for a robotic arm. The goal is to let the robot recognize parts on a work cell, decide how to grasp them, and place them accurately, with minimal manual programming.The project involves building a solution capable of:Detecting and identifying the parts used in the cell with a trained object detector.Estimating grasp poses directly from camera images.Calibrating the camera with the robot arm (hand-eye calibration) for precise positioning.Planning collision-free arm motions to pick and place each part.Measuring success rate, speed and accuracy in simulation and on the real cell.Technical SkillsExperience with Python or C++.Computer vision skills with OpenCV.Deep learning basics for object detection (PyTorch, YOLO).Understanding of robot kinematics and coordinate frames.

We are looking for a Robotics Engineering Intern to build an autonomous mobile robot that can map indoor spaces, navigate safely around people and obstacles, and understand simple spoken or written instructions. The goal is to move from simulation to a working physical robot with intelligent, natural-language navigation.The project involves building a solution capable of:Mapping and localizing in indoor spaces with SLAM, using LiDAR and cameras.Detecting and avoiding obstacles in real time.Understanding natural-language goals like "go to meeting room B" with vision-language navigation.Labeling rooms and objects on the map with semantic segmentation.Being validated in simulation first, then deployed and benchmarked on a physical robot.This internship provides hands-on experience in robotics, perception and AI-driven navigation.Technical SkillsSolid Python or C++.Experience with ROS or ROS 2 from coursework or projects.Understanding of SLAM, localization and path planning.Basic computer vision knowledge.

We are looking for a Machine Learning Engineering Intern to build a predictive maintenance solution that anticipates equipment failures before they happen. The goal is to help industrial teams reduce downtime and maintenance costs by turning sensor data into early warnings and clear recommendations.The project involves building a solution capable of:Collecting and cleaning sensor data through a pipeline with automated quality checks.Forecasting equipment behaviour and detecting anomalies on time-series data.Estimating failure risk and raising alerts with severity levels.Showing asset health, trends and alerts in a monitoring dashboard.Technical SkillsSolid Python and data libraries (pandas, NumPy, scikit-learn).Understanding of time-series analysis and forecasting.Basic knowledge of SQL and data pipelines.Familiarity with Git and Docker.Tech StackData & ML: Python, pandas, scikit-learn, Prophet or PyTorchStorage: PostgreSQL or TimescaleDBMLOps: MLflow, Evidently, DockerDashboards: Grafana or StreamlitTools: Git, GitHub Actions

We are looking for a Mobile Development Intern to build an offline-first field app with built-in AI assistance, designed for teams working on-site with weak or no connectivity. The goal is to let field workers capture data reliably anywhere, while an AI assistant helps them work faster and make fewer mistakes.The project involves building a solution capable of:Storing data locally and queuing changes while offline.Synchronizing data with the backend automatically when the connection returns, with conflict handling.Offering an AI assistant that drafts field reports and checks entries for errors.Providing a simple, reliable mobile experience for field teams.Using AI-assisted code review and test generation during development, and documenting where the assistant helped.This internship provides hands-on experience in mobile development, offline-first architecture and AI-assisted software engineering.Technical SkillsExperience with at least one mobile or web framework (React Native preferred).Solid JavaScript/TypeScript.Understanding of REST APIs and local storage (SQLite or similar).Familiarity with Git.Bonus Skills (Not Required but Appreciated)Experience with offline sync tools (WatermelonDB, RxDB, PouchDB).Experience integrating LLM APIs into apps.Use of AI coding assistants (GitHub Copilot, Claude Code, Cursor).Tech StackMobile: React Native, TypeScriptOffline storage & sync: SQLite, WatermelonDB or similarBackend: Node.js or FastAPI, PostgreSQLAI: LLM APIs, AI coding assistantsTools: Git, GitHub Actions, Jest

We are looking for an AI Engineering Intern to build a multimodal knowledge assistant that can search and answer questions across every type of company content, not just text. The goal is to let users find answers hidden in scanned documents, tables, charts, images and recordings, with clear citations they can trust.The project involves building a solution capable of:Ingesting and indexing text, scanned PDFs, tables, charts, images and audio in one shared retrieval space.Parsing document layouts and transcribing audio to make all content searchable.Answering questions that combine several media types using vision-language models.Citing sources precisely: the exact page, image region or audio timestamp.Benchmarking retrieval and answer quality per media type, and tuning for speed and cost.This internship provides hands-on experience in multimodal AI, retrieval systems and LLM evaluation.Technical SkillsSolid Python and experience with PyTorch or Hugging Face.Understanding of embeddings, vector search and RAG.Experience with LLMs or vision models from coursework or projects.Basic knowledge of APIs and Docker.Bonus Skills (Not Required but Appreciated)Experience with vision-language models (Qwen-VL, ColPali).Knowledge of OCR and layout parsing tools (Docling, PaddleOCR).Familiarity with speech-to-text (Whisper).Tech StackModels: Qwen2.5-VL, ColPali, CLIP/SigLIP, WhisperParsing: Docling, PaddleOCRSearch: Qdrant or Vespa (multi-vector)Backend: Python, FastAPIEvaluation & tools: RAGAS, Docker, Git

We are looking for an AI Engineering Intern to build a sovereign AI assistant that lets organizations search, understand and summarize their internal knowledge securely, with all models and data kept within their own infrastructure. The goal is to deliver a trusted, bilingual assistant for government and enterprise teams.The project involves building a solution capable of:Answering questions in Arabic and English, tuned to institutional terminology.Retrieving information across policies, circulars and archives with a hybrid RAG pipeline (semantic + keyword search, re-ranking).Summarizing documents and extracting key insights, with citations to the source.Running fully on-premise with self-hosted, optimized LLMs.Enforcing encryption, role-based access control and complete audit trails for every query and document interaction.This internship provides hands-on experience in LLM engineering, retrieval systems and secure AI deployment.Technical SkillsSolid Python and experience with LLM frameworks (LangChain or LlamaIndex).Understanding of RAG, embeddings and vector databases.Experience building REST APIs (FastAPI or similar).Basic knowledge of Docker and Linux.Bonus Skills (Not Required but Appreciated)Experience with Arabic NLP or multilingual models.Knowledge of LLM serving and quantization (vLLM, GPTQ, AWQ).Familiarity with LLM evaluation and guardrails (RAGAS, Llama Guard).Tech StackLLM & RAG: LangChain or LlamaIndex, vLLM, open-source LLMsSearch: Qdrant or pgvector, BM25, re-rankersBackend: Python, FastAPI, PostgreSQLSecurity: Keycloak (RBAC), encryption, audit loggingDevOps: Docker, Git, on-premise GPU servers

We are looking for a Content Marketing & Analytics Intern to build a content performance engine that shows what content works, why it works, and what to publish next. The goal is to help the marketing team plan content with data instead of intuition.The project involves building a solution capable of:Analysing topics, themes and sentiment in existing content with NLP and topic modeling.Tracking search visibility, keyword rankings and organic traffic over time.Identifying content gaps and opportunities compared with competitors.Scoring content opportunities by potential impact.Producing a monthly content plan with clear priorities in a shared dashboard.This internship provides hands-on experience in SEO analytics, NLP for marketing and data-driven content strategy.Technical SkillsUnderstanding of SEO concepts (keywords, rankings, search visibility).Basic Python for text analysis (pandas, NLP libraries).Familiarity with Google Search Console and Google Analytics.Strong writing skills in English (French is a plus).Bonus Skills (Not Required but Appreciated)Experience with SEO tools (Semrush, Ahrefs).Knowledge of topic modeling (BERTopic, LDA).Exposure to dashboard tools (Looker Studio, Power BI).