Internship - Data Science - Innovation And Assessment Of ai H/F CMA CGM

YOUR ROLE

The Data Science team designs and evaluates AI solutions to support business units, IT, and operations. It conducts POCs, defines evaluation frameworks, and assists product teams with industrialization (quality, cost, security, compliance). In collaboration with Platform/IT, Cybersecurity, and Legal/GDPR teams, it ensures responsible and measurable deployments.
The intern will contribute to technological exploration work (SLM/LLM, RAG, agents, XAI) and the presentation of results to decision-makers.

WHAT ARE YOU GOING TO DO ?

Assessment of emerging AI technologies (SLM/LLM, RAG, agents, MLOps tools):
You will conduct POCs, benchmarks, and scorecards, and produce clear deliverables (memos, decks, demos) to support "build vs. buy" decisions.

You will:

- Conduct structured technology watch (SLM/LLM, multimodal, vector DBs, RAG, agents/orchestration, evaluation, MLOps).

- Define use cases and success criteria (quality, latency, robustness, cost, security, compliance, UX).

- Prototype POCs in Python (Jupyter), integrate model APIs and tools (embeddings, retrieval).

- Set up benchmarks and comparison dashboards (scorecards, TCO/ROI, risk assessments).

- Perform fine-tuning (e.g., LoRA/QLoRA) and document cost/performance footprints.

- Apply XAI techniques (SHAP/LIME, saliency/attention analysis, counterfactuals), and produce model cards.

- Build evaluation pipelines (A/B testing, quality metrics, robustness, hallucination detection).

- Ensure experiment traceability and security (Git, experiment tracking, basic MLOps best practices).

- Deliver tailored presentations (memos, slides, internal wiki, mini demos) for both technical and non-technical audiences.

- Collaborate cross-functionally with Product, IT/Platform, Cybersecurity, and Legal/GDPR teams.

WHO ARE WE LOOKING FOR ?

- You are currently pursuing a Master's degree (M1/M2) or equivalent in Computer Science, Data/AI, Applied Mathematics, or Engineering.

- Previous experience in computer science or data science is a plus.

- You are proficient in key tools and concepts:

- Python (Jupyter), pandas, Git, API integration.

- SLM & LLM: prompting, cost/latency/quality tradeoffs, RAG basics, simple agents.

- Fine-tuning (LoRA/QLoRA), hyperparameter management, experiment tracking.

- XAI: SHAP/LIME, attention/saliency analysis, counterfactuals, good reporting practices.

- MLOps notions: Docker, at least one cloud provider, basic CI/CD, security & GDPR awareness.

- You have strong communication skills, both written and oral, and can produce clear scorecards and executive-level presentations in French and English.

- You demonstrate scientific rigor with attention to reproducibility and measurement.

- You have a good sense of pedagogy and are able to apply data storytelling effectively.

- You show both autonomy and a strong team spirit.

- Your English is operational.

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