Veolia

About the Company

Veolia group aims to be the benchmark company for ecological transformation. With nearly 220,000 employees worldwide, the Group designs and provides game-changing solutions that are both useful and practical for water, waste and energy management. Through its three complementary business activities, Veolia helps to develop access to resources, preserve available resources, and replenish them. In 2021, the Veolia group supplied 79 million people with drinking water and 61 million people with wastewater service, produced nearly 48 million megawatt hours of energy and treated 48 million metric tons of waste. Veolia Environnement (listed on Paris Euronext: VIE) recorded consolidated revenue of €28.508 billion in 2021.
----
Le groupe Veolia a pour ambition de devenir l’entreprise de référence de la transformation écologique. Présent sur les cinq continents avec près de 220 000 salariés, le Groupe conçoit et déploie des solutions utiles et concrètes pour la gestion de l’eau, des déchets et de l’énergie qui participent à changer radicalement la donne. Au travers de ses trois activités complémentaires, Veolia contribue à développer l’accès aux ressources, à préserver les ressources disponibles et à les renouveler. En 2021, le groupe Veolia a servi 79 millions d’habitants en eau potable et 61 millions en assainissement, produit près de 48 millions de mégawattheures et valorisé 48 millions de tonnes de déchets. Veolia Environnement (Paris Euronext : VIE) a réalisé en 2021 un chiffre d’affaires consolidé de 28,508 milliards d’euros.

Listed Jobs

Company Name

Veolia

Job Title

Customer Care Advisor

Job Description

Job Title: Customer Care Advisor Role Summary: Serve as the primary point of contact for customers, managing enquiries through phone, email, live chat, and web. Provide effective troubleshooting, maintain accurate service data, and identify sales opportunities while reflecting high standards of customer service and advocacy. Expectations: - Deliver professional, empathetic, and confident support. - Resolve issues efficiently, escalating appropriately. - Maintain precise logging and documentation. Key Responsibilities: - Handle incoming customer enquiries and manage expectations. - Resolve customer issues and service requests; log details accurately. - Provide basic technical troubleshooting and facilitate service registration. - Validate order details and coordinate with internal teams. - Identify and pursue sales opportunities and quotation requests. Required Skills: - Excellent communication and telephone etiquette. - Strong organisational, attention‑to‑detail, and problem‑solving abilities. - Proficiency with Microsoft Office and Google Suite. - Team‑work orientation with a passion for customer service. Required Education & Certifications: - GCSE (or equivalent) in English and Maths. - Prior experience in customer service, call center, sales support, or administration.

Bourne end, United kingdom

On site

03-02-2026

Company Name

Veolia

Job Title

Intern - AI Engineering SLM

Job Description

**Job Title** Intern – AI Engineering SLM **Role Summary** Support the design, build, test, deploy, and monitor of small language model (SLM) applications for enterprise use. Apply cutting‑edge lightweight models (e.g., Phi‑3, Llama, Mistral, Gemma, TinyLlama) and associated tooling (LangChain, vLLM, ChromaDB, FastAPI). Deliver production‑ready solutions on edge, local, or cloud platforms while collaborating with senior AI engineers and stakeholders. **Expactations** - Complete end‑to‑end SLM application development within a 12‑week rotation. - Demonstrate proficiency with model selection, fine‑tuning, prompt engineering, and RAG pipelines. - Produce clean, version‑controlled code and document experiments. - Participate in sprint reviews and knowledge‑sharing sessions. **Key Responsibilities** 1. Gather functional requirements and design UI/UX workflows in Figma. 2. Explore, clean, and analyze data using Jupyter, pandas, and notebooks. 3. Select and download pre‑trained SLMs from Hugging Face Model Hub; benchmark performance. 4. Develop application logic with LangChain or Lanngraph, orchestrating workflows. 5. Fine‑tune models with PEFT (LoRA/QLoRA) via Hugging Face Transformers. 6. Implement semantic search and RAG with ChromaDB and evaluate outputs. 7. Build RESTful APIs using FastAPI (Python) or Express.js (Node.js). 8. Containerize workloads with Docker; release on Kubernetes or Docker Swarm. 9. Create and run unit, model, and load tests (pytest, RAGAS, DeepEval, Locust). 10. Log experiments with MLflow/Weights & Biases and track data with DVC. 11. Monitor and observe application performance through LangSmith and APIGateway tools. 12. Deploy on chosen infrastructure (on‑premise, GCP Vertex AI, or hybrid edge). **Required Skills** - Programming: Python, Git, VS Code. - AI/ML: Familiarity with small language models, Hugging Face, LangChain, vLLM. - Data handling: pandas, Jupyter. - Model fine‑tuning: LoRA, QLoRA, Hugging Face Transformers. - Prompt engineering: LangSmith, PromptLayer. - API development: FastAPI or Express.js. - Testing frameworks: pytest, unittest, RAGAS, DeepEval, Locust. - Containerization: Docker, Docker Compose. - Orchestration: Kubernetes (K8s), Docker Swarm. - CI/CD: GitHub Actions, GitLab CI. - Experiment tracking: MLflow, Weights & Biases. - Version control: Git, DVC. - Cloud basics: GCP Vertex AI or equivalent. - Communication: strong written and verbal skills. **Required Education & Certifications** - Pursuing a Ph.D. (or equivalent advanced degree) in AI/ML/Computer Science. - Minimum cumulative GPA of 3.8. - No additional certifications required, but knowledge of cloud provider (GCP, AWS, Azure) is advantageous.

Paramus, United states

On site

Fresher

20-02-2026

Company Name

Veolia

Job Title

Data Science Intern

Job Description

Job Title: Data Science Intern Role Summary: 12‑week SEED internship applying generative AI (LLMs, prompt engineering, multimodal models) to solve business problems and increase operational efficiency within a sustainability‑focused organization. Expectations: Deliver functional AI agents, optimize prompt strategies, present findings to technical and non‑technical stakeholders, stay current on AI trends and ethical practices, and collaborate cross‑functionally. Key Responsibilities: - Create, configure, and test AI agents using LLMs to address specific business challenges. - Develop and refine prompt engineering strategies and evaluation metrics. - Monitor and integrate emerging generative‑AI models, tools, and best practices. - Work with cross‑functional teams to translate business needs into AI‑driven solutions. - Prepare and present analytical reports and model outcomes to stakeholders. Required Skills: - Proficiency in Python programming. - Experience with SQL and data querying. - Version control using Git. - Familiarity with LLMs (GPT, Gemini, Claude, LLaMA, etc.) and their trade‑offs. - Knowledge of prompt engineering, multimodal models, and agentic AI design. - Basic understanding of Retrieval‑Augmented Generation (RAG). - Ability to use APIs for LLMs and other AI services. - Comfort with cloud platforms (e.g., GCP). - Strong analytical and problem‑solving abilities. - Excellent verbal and written communication skills. - Awareness of ethical considerations in generative AI. - Self‑managed and detail‑oriented work style. Required Education & Certifications: - Currently pursuing or completed a Master’s degree in Computer Science or a related field.

Paramus, United states

Hybrid

Fresher

23-02-2026

Company Name

Veolia

Job Title

Stage Deep learning pour la détection et le suivi de camions

Job Description

Job Title: Deep Learning Internship – Truck Detection & Tracking Role Summary: Assist in developing robust deep‑learning methods for detecting and re‑identifying trucks across multiple camera feeds on industrial sites. Focus on applying state‑of‑the‑art computer vision models to real‑time image data to improve truck flow monitoring and traceability. Expectations: - Conduct literature review of existing deep‑learning models for vehicle detection and re‑identification. - Implement and fine‑tune CNN‑based detection and re‑identification pipelines. - Evaluate model performance and optimize accuracy, speed, and robustness on collected image datasets. - Collaborate with a multidisciplinary team to integrate solutions into site operations. Key Responsibilities: 1. Review academic and industry literature on vehicle detection and re‑identification. 2. Design, prototype, and train deep‑learning models for truck detection. 3. Develop re‑identification models to match the same truck across discontinuous camera views. 4. Perform evaluation metrics (precision, recall, mAP, ID‑F1) and iterate to meet performance targets. 5. Document methodology, code, and results for internal knowledge transfer. 6. Communicate progress and findings to team members and stakeholders. Required Skills: - Proficiency in Python and deep‑learning frameworks (TensorFlow/Keras, PyTorch). - Experience with convolutional neural networks for object detection (e.g., YOLO, Faster‑R‑CNN). - Knowledge of re‑identification architectures (triplet loss, Siamese networks). - Familiarity with image‑processing libraries (OpenCV, scikit‑image). - Strong analytical and problem‑solving abilities. - Excellent written and verbal communication in English. Required Education & Certifications: - Currently pursuing Master’s (MSc) or final year of Engineering (BAC+5) in Data Science, Computer Vision, Computer Engineering, Statistics, or Deep Learning.

Aubervilliers, France

On site

04-03-2026