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Lynx Financial Crime Tech is an AI-powered software company specializing in detecting and predicting behavioral patterns for fraud prevention and anti-money laundering (AML). The company is led by experts from the financial and academic sectors and develops cutting-edge AI and machine learning technologies. Their platform excels in low-latency transaction processing and is available both on-premises and in the cloud.
As an AI/ML Engineer, you will participate in developing advanced artificial intelligence and machine learning solutions focused on creating sophisticated models for decision-making and solving business problems. Key responsibilities include:
• Analyzing requirements and participating in the design of AI components to enhance existing solutions or create new ones
• Developing, training, and validating Machine Learning and Artificial Intelligence models
• Conducting exploratory data analysis and selecting relevant variables for ML model creation
• Designing and configuring AI agent systems
• Fine-tuning, specializing, and optimizing Large Language Models (LLMs)
• Testing, evaluating, and continuously improving the performance, robustness, and accuracy of solutions
• Diagnosing incidents, analyzing results, and optimizing existing models
• Implementing improvements and adopting best practices in Data Science, Machine Learning, and MLOps
You will work in an international, specialized environment where you can grow, innovate, and develop with purpose, contributing to a safer and more transparent financial system. The company prioritizes vision, agility, and speed to deliver exceptional customer experiences and has established lasting, trusted relationships with leading financial institutions, fintechs, and commercial enterprises worldwide.
The role is hybrid-based in Madrid with a collaborative team focused on data and AI applied to fraud and AML.
**REQUIREMENTS:**
Professional Experience:
• 5+ years developing Machine Learning models and Artificial Intelligence solutions (mandatory)
Academic Background:
• Double degree in Computer Engineering + Mathematics with specialization in artificial intelligence (master's or demonstrable experience)
• Graduates in Data Science
• Graduates in other engineering disciplines, Mathematics, Statistics, Physics, or similar fields, complemented with solid programming knowledge
Languages:
• Fluent English, minimum B2 level (desirable)
Mandatory Technical Skills:
• Knowledge of Generative and Agentic AI technologies: LLMs, RAG, MCP, multi-agent systems tools
• Development experience with AI agent frameworks such as LangChain, LangGraph, Google ADK, or similar
• Consolidated knowledge of supervised and unsupervised Machine Learning techniques
• Experience developing models with Python and libraries such as Scikit-learn, Pandas, and NumPy
• Experience with software development techniques and strategies: git, CI/CD pipeline implementation (e.g., GitHub Actions), branch development
• Solid knowledge of applied statistics and model evaluation
• Experience working with SQL and data processing
• Experience with data analysis and visualization techniques
• Knowledge of Deep Learning libraries such as TensorFlow, PyTorch, or Keras
Desirable Technical Skills:
• Experience with tools for model packaging and serving: REST APIs, Docker
• AWS knowledge and certifications
• Knowledge of generative model specialization techniques: SFT, quantization, distillation
• Experience or familiarity with MLOps practices
