Top Machine Learning Jobs in Spain

End-to-end delivery of ML-powered services, involving research, prototyping, production, and operations. Collaborate on product requirements while maintaining high quality and operational excellence.

The role involves designing, training, and optimizing ML models for document intelligence using traditional and modern techniques, focusing on document automation and structured data extraction.

Design, deploy, and monitor production ML models and pipelines; improve Python and SQL code for data transformation and feature engineering; prototype LLM, RAG, and agentic AI solutions; build Streamlit interfaces; collaborate with product and engineering teams and communicate results to stakeholders.

Lead the ML platform strategy and development, manage teams, drive MLOps adoption, and influence stakeholders in a global organization.

Lead the development of robot policies, focusing on task planning, computer vision, and decision-making in robotics. Mentor teams, drive technical roadmaps, and collaborate on scalable AI solutions.

The Senior Robotics AI/ML Engineer at Analog Devices will develop AI-based robot policies, work on task planning and computer vision, and integrate AI into robotics systems, while collaborating with multidisciplinary teams.

Lead the Applied AI Team in developing and deploying ML systems for clinical care, mentoring engineers, and driving initiatives across the AI stack.

The Data Scientist/ML Engineer will analyze data, develop data science solutions, and collaborate with teams to enhance ad effectiveness while optimizing machine learning models.

Own and drive ML solutions for clinical care at scale, including LLM fine-tuning and production deployment, collaborating across teams.

The AI/ML Engineer will develop and implement ML systems for secure-code understanding, manage infrastructure for LLMs, optimize models, and conduct research.

This role involves designing and maintaining machine learning pipelines, integrating models, optimizing infrastructure, and collaborating on AI projects.

As a Lead Machine Learning Engineer, you will oversee complex projects, mentor teams, drive ML practices, and shape technical strategy.

The Senior Machine Learning Engineer will design and manage ML pipelines, automate CI/CD for ML systems, and monitor production models. The role requires strong Python skills, familiarity with ML lifecycle, and collaboration with the ML team.

As a Machine Learning Senior Engineer, you will develop algorithms, enhance pipelines, analyze data, and mentor team members while solving unique modeling challenges.

The Machine Learning Engineer will design, develop, and validate predictive models and algorithms, ensuring scalability and compliance with data governance in collaboration with various teams.

Responsible for the end-to-end lifecycle of ML solutions focusing on API development and full-stack engineering, utilizing advanced ML libraries and LLMs.

As a Lead Machine Learning Engineer, you will design ML infrastructure, mentor engineers, and ensure deployment reliability while collaborating across teams.

Design scalable ML solutions and guide customers from concept to production. Collaborate with leaders and teams to achieve impactful AI outcomes.

As a Senior Software Engineer in AI/ML, you'll design, develop, and enhance software for autonomous robotic inspections, optimize ML systems, and collaborate with cross-functional teams.

Lead the vision and strategy for Delivery Hero's ML platform, focusing on MLOps implementation, team management, and stakeholder engagement.

The role focuses on designing, implementing, and optimizing machine learning solutions, improving data workflows, and enhancing customer experiences.

As a Machine Learning Engineer, you will develop and improve algorithms, implement scalable solutions, and analyze data to provide business insights.

We are seeking a Senior ML/AI Engineer to build secure, scalable systems and deploy applications using machine learning, specifically in LLM. Responsibilities include architecting multi-agent systems, building data processing pipelines, and collaborating with teams.

Design and implement ML platform capabilities: observability, cost and training efficiency, experimentation tooling, and SaaS-grade ML services in Python. Collaborate with Staff Engineer and SRE/DevXP to deliver production-ready, scalable, and developer-friendly infrastructure for data scientists.

Own and evolve Preply's ML platform: design experiment tracking, artifact management, GPU training and scalable inference, CI/CD for ML, observability, and LLM/RAG capabilities while mentoring engineers and aligning platform delivery with product goals.