Daniel – Python, LLM, AI agent development

AI consulting company delivering end-to-end artificial intelligence solutions for clients across multiple industries.

• Led the end-to-end delivery of Data Science and AI solutions across multiple industries, from discovery to production rollout;
• Built and shipped business chatbots and assistants using OpenAI APIs and open-source LLMs and integrated them with internal data sources and workflows;
• Designed LLM pipelines with a production mindset and implemented retrieval-based grounding patterns, including document ingestion, chunking strategies, embeddings, and vector search to improve answer faithfulness and reduce hallucinations;
• Developed supervised machine learning models for credit risk assessment, forecasting, and optimization use cases and validated them using robust metrics and error analysis;
• Built analytics web platforms, including complex ETL pipelines and advanced data visualizations, to operationalize insights for business users;
• Delivered NLP solutions for HR and Computer Vision systems for defect or malfunction detection, object tracking, and damage assessment;
• Implemented AI voice solutions for contact centers and integrated them into operational processes.

AI startup developing products for the blockchain ecosystem.

• Co-founded an early-stage startup focused on AI products in the blockchain ecosystem;
• Defined the technical roadmap, built prototypes and MVPs, and evaluated the feasibility of AI-driven use cases.

AI solutions for industrial predictive maintenance, process optimization, and IoT applications.

• Led the development of artificial intelligence algorithms applied to industrial predictive maintenance and optimization of industrial processes to build IoT solutions;
• Designed pipelines for sensor and time-series analytics, anomaly detection, and early warning systems to reduce downtime and improve operational efficiency;
• Partnered with engineering teams to integrate models into production workflows and ensure reliable data and feature availability;
• Established validation practices and monitoring indicators to track model performance after deployment.

Applied AI and advanced analytics initiatives across multiple industries, spanning computer vision, recommendation systems, NLP, knowledge extraction, and anomaly detection, including production applications serving millions of daily users.

• Served as the technical director of R&D projects carried out in Spain within the World Class Center for Analytics;
• Contributed to advanced analytics solutions for customer and R&D projects across multiple sectors;
• Developed artificial vision systems using deep learning techniques;
• Created complex content-based recommendation engines;
• Delivered NLP, NLU, and NLG solutions and generated knowledge graphs from unstructured data;
• Created reinforcement learning algorithms for improving concurrent multi-user systems;
• Built anomaly detection solutions for industrial sensors and medical signals;
• Developed realistic data simulation solutions through generative adversarial networks;
• Researched and developed state-of-the-art algorithms in multi-agent classification systems;
• Deployed machine learning algorithms in production for millions of daily users in AWS using EMR, EC2, DynamoDB, S3, and Lambda;
• Developed cartographic analysis libraries.