Senior Machine Learning Engineer, hibrido EPAM Madrid, España Senior Machine Learning Engineer Were looking for a Senior ML Engineer to join our team in Madrid, Spain in a hybrid working mode.
In this role, you will design, build, and deploy scalable machine learning and AI solutions that power next

- generation digital capabilities within a leading general financial institution.

You will work across the full lifecycle

- from concept and prototyping to production
- in an agile and Dev Ops-oriented environment, collaborating with multi-disciplinary teams to deliver robust, business-critical AI systems.

If you are passionate about Large Language Models, multi-agent workflows, and advanced ML engineering practices, this is an opportunity to shape AI-driven innovation within one of the worlds most renowned wealth management organizations.
Responsibilities Design, develop, deploy, and optimize machine learning and AI solutions addressing complex business challenges
Build and integrate multi-agent systems and enable AI models with function/tool calling capabilities
Design and maintain RAG (Retrieval-Augmented Generation) systems to ground AI outputs in enterprise data
Integrate and fine-tune Large Language Models (LLMs) to ensure performance, consistency, and reliability
Optimize agentic workflows for production use cases while ensuring safety and accuracy
Evaluate and improve system performance using robust metrics, evaluation sets, and continuous iteration
Collaborate with data engineers, platform teams, and data scientists to integrate ML solutions into enterprise systems




Conduct code reviews, unit testing, and debugging to guarantee quality and maintainability
Ensure compliance with software development best practices across version control, testing, and documentation
Requirements Bachelors or Masters degree in Data Science, Computer Science, Mathematics, Statistics, or related field
Proven experience as a Machine Learning Engineer or similar role in AI solution development
Strong programming skills in Python, experience with ML libraries and deep learning frameworks (Tensor Flow or PyTorch)
Practical experience implementing and deploying LLMs and related orchestration frameworks
Knowledge of agentic workflows, multi-agent systems, and advanced reasoning patterns
Strong understanding of data preprocessing, feature engineering, and model evaluation techniques
Deep familiarity with relevant mathematical and statistical concepts (probability, linear algebra, optimization)
Experience implementing MLOps practices and working in Dev Ops-based environments
Excellent problem-solving, debugging, and optimization skills
Strong communication and ability to collaborate with cross-functional teams in an agile environment
Nice to have Experience designing RAG systems for enterprise-scale use
Prior exposure to AI governance, security, or compliance in financial services
Familiarity with cloud infrastructures and containerized ML deployments using Kubernetes
Proven track record of enabling AI-driven applications in production environments

Machine Learning, RAG, LLM, Python

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📌 Senior Machine Learning Engineer, Hibrido (Madrid)
🏢 Epam
📍 Madrid