Design, develop & deploy ML/LLM models, data pipelines & agentic AI solutions for int/ext projects

OUTSCALE; Saint-Cloud; Sur place; EUR 70 000 - 110 000; Plein temps

Résumé du poste

Dassault Systèmes is seeking a skilled Data Scientist to advance AI solutions across NLP, Computer Vision, and LLM domains. You will contribute to research-to-production pipelines, working with unstructured data and scalable Python code.

Responsibilities include benchmarking, algorithm design, and deploying AI services via containerized cloud environments. Fluency in French and English is expected for daily communication within the team.

Qualifications

• Proficient in Python with hands-on DL/LLM frameworks (PyTorch, TensorFlow, Hugging Face).
• Strong understanding of neural networks, ML techniques and data processing methods.
• Ability to develop production-grade code and deploy AI solutions.

Responsabilités

• Analyze complex business and technical problems and propose AI solutions.
• Lead benchmarking and evaluation studies for models and approaches.
• Design, implement, and evaluate ML/DL algorithms.
• Process large unstructured data (text and images).
• Develop production-grade Python code and APIs for AI services.

Connaissances

Python programming

Deep Learning

ML fundamentals

NLP

Computer Vision

LLMs

Outils

Docker

Kubernetes

PyTorch

TensorFlow

Hugging Face

CUDA

ONNX

MLflow

Weights & Biases

Description du poste

You will join our DataScience team, which focuses on the research and development of AI solutions built on DL, NLP, Computer Vision,LLMs and agentic AI.

We work on cuttingedge AI projects, tackling complex challenges related to the processing of textual and visual data in order to meet the needs of a variety of business use cases.

The team drives projects from research to production, collaborating actively with a range of internal and external teams.

Working as part of the team, you will contribute to the following activities:

• Analyze complex business and technical problems and propose innovative AI solutions.
• Lead benchmarking and evaluation studies to assess models, algorithms, and approaches.
• Design, implement, and evaluate machine learning and deep learning algorithms.
• Process and leverage large volumes of unstructured data, including text and images.
• Develop maintainable, tested, production-grade Python code.
• Optimize DL and LLM models for scalability, efficiency, and performance.
• Productionize algorithms and models as robust, scalable API services.
• Containerize and deploy AI services to cloud environments.
• Write and maintain technical and scientific specifications, documentation, and experiment reports.
• Proficient in Python: Strong Python skills, with hands-on experience using Deep Learning and LLM frameworks and libraries such as PyTorch, TensorFlow, and Hugging Face.
• Strong ML fundamentals: Solid understanding of neural network architectures, machine learning techniques, and methods for data analysis, processing, and transformation.
• Business-oriented mindset: Interested in solving concrete business problems and applying AI expertise to a variety of real-world use cases.
• Cloud & deployment: Knowledge of deploying AI solutions to the cloud, including Docker, Kubernetes, cloud services, and related infrastructure, is a strong plus.
• Production-grade development: Able to write clean, maintainable, tested, and production-grade Python code.
• Curiosity & ownership: Motivated to learn, organized, curious, open-minded, and proactive, with strong problem-solving and interpersonal skills.
• Teamwork: Able to work effectively in a collaborative, multidisciplinary, and innovative environment.

Languages: Fluent in French and English, both written and spoken. Daily team communication is in English.

Technical Stack

• Language & frameworks: Python 3.11, PyTorch
• GPU acceleration: CUDA, NVIDIA GPU drivers
• ML/LLM libraries: Hugging Face Transformers, torch.nn, ONNX, etc.
• LLM inference & serving: vLLM, NVIDIA Triton Inference Server
• Domains: NLP, Computer Vision, state-of-the-art (SOTA) LLMs
• LLM applications: RAG, Graph RAG, Vector Databases
• Experiment tracking: MLflow, Weights & Biases (W&B)
• Containerization: Docker; Kubernetes is a plus
• APIs: REST
• Infrastructure & tooling: Linux, Git, CI/CD

Inclusion statement

As a game-changer in sustainable technology and innovation, Dassault Systèmes is striving to build more inclusive and diverse teams across the globe. We believe that our people are our number one asset and we want all employees to feel empowered to bring their whole selves to work every day. It is our goal that our people feel a sense of pride and a passion for belonging. As a company leading change, it’s our responsibility to foster opportunities for all people to participate in a harmonized Workforce of the Future.