Data Science/AI

Summary

Design and deploy AI/ML solutions—including GenAI, RAG architectures, and agentic AI—for a European financial group, using Python, LLMs, vector databases, and cloud platforms.

About the Role

Join a leading European financial group and work at the forefront of Artificial Intelligence and Machine Learning innovation. You will collaborate with multidisciplinary teams of data scientists, AI specialists, engineers, and product experts to design and deliver cutting-edge solutions that address real-world business challenges and create measurable impact.


Key Responsibilities

  • Design and Deploy AI Solutions: Develop, train, and deploy machine learning models and advanced AI applications tailored to business needs.
  • Develop Generative AI Capabilities: Fine-tune, customize, and optimize both open-source and commercial Large Language Models (LLMs).
  • Implement RAG Architectures: Design and enhance Retrieval-Augmented Generation (RAG) solutions to improve accuracy, scalability, and efficiency.
  • Perform Advanced Data Analysis: Conduct exploratory data analysis, feature engineering, and data preparation to maximize model performance.
  • Build Agentic AI Solutions: Design and implement intelligent agent-based systems, leveraging Agent Harness concepts (memory, state management, storage, file systems), MCP ecosystems (servers, tools, gateways, protocols), and agent communication standards such as A2A and ACP.
  • Apply Traditional Machine Learning Techniques: Utilize classification, regression, clustering, decision trees, SVMs, neural networks, and other AI techniques to solve complex business problems.
  • Collaborate Across Teams: Partner closely with data engineers, product managers, business stakeholders, and technical teams to deliver high-impact solutions.
  • Ensure Solution Quality: Establish robust testing, validation, monitoring, and evaluation processes to ensure reliable and high-performing AI systems.
  • Document and Share Knowledge: Maintain clear technical documentation and contribute to knowledge-sharing initiatives to support scalability and reproducibility.


Required Qualifications

  • Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, or a related field.
  • Minimum of 3 years of hands-on experience in Machine Learning and AI development.
  • Proven experience designing and deploying agentic AI solutions in production environments.
  • Strong expertise in both open-source and commercial Large Language Models.
  • Hands-on experience implementing Retrieval-Augmented Generation (RAG) frameworks.
  • Experience working with vector databases and semantic search technologies.
  • Advanced Python programming skills, with practical experience in frameworks such as TensorFlow, PyTorch, and Hugging Face.
  • Solid understanding of Natural Language Processing (NLP) techniques, architectures, and applications.
  • Strong foundation in traditional machine learning algorithms, including decision trees, SVMs, clustering methods, and neural networks.
  • Experience deploying AI/ML solutions on cloud platforms such as AWS, Azure, or Google Cloud Platform.
  • Familiarity with MLOps methodologies, tools, and best practices.
  • Strong analytical thinking, problem-solving abilities, and attention to detail.
  • Excellent communication, presentation, and collaboration skills.
  • Fluent English (C1 level or higher) is mandatory.
  • Willingness to learn French.


What We Offer

  • The opportunity to work on innovative AI and Generative AI initiatives within a major European financial institution.
  • Exposure to state-of-the-art technologies, large-scale AI platforms, and enterprise-grade solutions.
  • A collaborative and international environment focused on innovation, learning, and professional growth.
  • The chance to contribute to the next generation of AI-powered products and services.


See also

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