Python Machine Learning Engineer (Hybrid - Madrid)
Indexed description
What we look for?
A passionate Machine Learning Engineer with experience in Generative AI, Large Language Models (LLMs), AI Agents, and MLOps/DevOps environments, eager to help design, build, and deploy enterprise-grade AI solutions.
Required to go to the client's offices in central Madrid 3 days a week.
High english level is required.
Key Responsibilities
- Develop, deploy, and optimize Machine Learning and AI solutions for complex business challenges.
- Design and implement multi-agent systems and enable AI models with function/tool-calling capabilities.
- Build and maintain Retrieval-Augmented Generation (RAG) solutions using enterprise data.
- Evaluate, integrate, and optimize AI models, including Large Language Models (LLMs).
- Design and improve agentic workflows and AI agents for production environments.
- Test and optimize prompts and few-shot examples to ensure accurate, consistent, and safe AI outputs.
- Evaluate model performance using appropriate metrics, benchmarks, and validation techniques.
- Collaborate with Data Scientists, Data Engineers, Platform Teams, and other stakeholders.
- Participate in code reviews, testing, debugging, and quality assurance activities.
- Contribute to the full AI lifecycle, from design and development to deployment and monitoring.
- Bachelor’s or Master’s degree in Computer Science, Data Science, Mathematics, Statistics, or a related field.
- Strong programming skills in Python.
- Hands-on experience with Machine Learning frameworks such as TensorFlow and/or PyTorch.
- Proven experience working with Large Language Models (LLMs).
- Solid understanding of AI Agents, agentic workflows, orchestration frameworks, and reasoning patterns.
- Experience designing and implementing RAG architectures.
- Knowledge of data preprocessing, feature engineering, model selection, and evaluation techniques.
- Strong understanding of statistics, probability, linear algebra, and optimization concepts.
- Experience applying software engineering best practices, including version control, testing, and documentation.
- English C1
- Experience working in cloud environments (Azure, AWS, or GCP).
- Knowledge of MLOps and CI/CD practices.
- Experience deploying and monitoring AI solutions in production.
- Background in financial services, banking, or wealth management.
- Familiarity with vector databases and modern GenAI ecosystems.
- 23 days of Annual Leave plus the 24th and 31st of December as discretionary days!
- Numerous benefits (Heath Care Plan, Internet Connectivity, Life and Accident Insurances).
- `Retribución Flexible´ Program: (Meals, Kinder Garden, Transport, online English lessons, Heath Care Plan…)
- Free access to several training platforms
- Professional stability and career plans
- UST also, compensates referrals from which you could benefit when you refer professionals.
- The option to pick between 12 or 14 payments along the year.
- Real Work Life Balance measures (flexibility, WFH or remote work policy, compacted hours during summertime…)
- UST Club Platform discounts and gym Access discounts
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