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Paid Internship
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22Open Positions

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Internship: AI Developer - Analytics & Agentic AI - F/M

SAP
Found 1 month ago
Location
Levallois-Perret, France
Duration (Months)
6 Months
Time
Full-time
Work Mode
Hybrid
Salary
paid in line with the SAP gratification grid
Visa Help
Not disclosed
Last Verified
1 month ago

Education

  • Master

Skills & Qualifications

Technical Skills

  • Python
  • JavaScript/TypeScript
  • ML/Deep Learning
  • LLMs / transformer models
  • REST APIs
  • FastAPI
  • Flask
  • Django
  • Git/GitHub
  • Docker
  • Linux
  • cloud services
  • Hugging Face
  • OpenAI
  • RAG
  • vector databases
  • ChromaDB
  • Pinecone
  • Milvus
  • FAISS
  • embedding models
  • MLOps/LLMOps
  • MLflow
  • BentoML
  • agentic frameworks
  • LangChain
  • langgraph
  • Kubernetes

Soft Skills

  • team player
  • takes initiative
  • perseveres
  • stay curious
  • collaborative agile teamwork
  • Excellent communication skills

Job Description

First, you’ll be onboarded within the team to understand the SAP Business Data Cloud solution, our development culture and delivery process, then you’ll participate in the AI-based alternative of our Line of Business Query Designer. You will: • Prototype and implement AI components: LLM-powered pipelines, RAG, tool/agent integrations, and evaluation harnesses. • Implement backend services and APIs to expose AI capabilities (FastAPI/Flask or similar). • Develop and maintain CI/CD and MLOps pipelines to move PoCs to repeatable deployments (Jenkins, GitHub Actions, etc.). • Containerize and deploy components using Docker and Kubernetes (or local dev equivalents). • Help design, run, and analyze automated tests and evaluation metrics for model quality, hallucination, latency, and cost. • Collaborate with data engineers to build and maintain retrieval indices, embeddings pipelines, and feature stores. • Participate in design, sprint reviews, and cross-functional demos with product, QA, and UX. • Contribute to documentation, reproducible experiments, and internal enablement material.

Requirements

  • Final year of Master’s student in Computer Science, Engineering, Data Science, Artificial Intelligence or related field.
  • Strong Python programming skills; familiarity with JavaScript/TypeScript is a plus.
  • Experience or coursework with ML/Deep Learning fundamentals and at least basic exposure to LLMs / transformer models.
  • Familiarity with REST APIs and backend frameworks (FastAPI, Flask, Django).
  • Experience with Git/GitHub and collaborative software development workflows.
  • Basic knowledge of containers (Docker) and comfort using Linux and cloud services.
  • Interest in productionizing ML systems, good software engineering hygiene, and collaborative agile teamwork.
  • Excellent communication skills in English and French (at least B2 level in both)

Related Field

  • AI & Machine Learning

Related Subfield

  • Applied Machine Learning

Languages

  • English
  • French

Nice to Haves

  • Hands-on experience with Hugging Face, OpenAI, or other LLM platforms; prompt engineering and evaluation experience.
  • Familiarity with RAG approaches, vector databases (e.g., ChromaDB, Pinecone, Milvus or FAISS), and embedding models.
  • Exposure to MLOps/LLMOps tooling (MLflow, BentoML), observability, and cost-aware deployment.
  • Experience with agentic frameworks (LangChain, langgraph) or multi-tool orchestrations.
  • Knowledge of data engineering, Kubernetes, and cloud platforms.
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