Top Machine Learning Jobs in Madrid

The role involves leading a team of engineers in developing and deploying ML/AI solutions, focusing on LLMs on AWS, while ensuring technical execution and team growth.

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

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

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

Research and develop AI/ML models for handwriting recognition and related technologies, collaborating with a multidisciplinary team to deliver innovative features.

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

As a Senior AI/ML Engineer at Crypto Banter, you will develop a market intelligence system that correlates social media signals with cryptocurrency price movements, leveraging natural language processing and real-time data.

As a Senior Software Engineer, you'll create advanced AI systems to improve developer productivity, integrate existing tools, and mentor junior engineers.

Leading complex, cross-functional projects in machine learning, managing stakeholder communications, risk mitigation, and ensuring production readiness.

The Robotics ML Engineer will build AI-first robotics projects and data pipelines, create educational content, and interact with customers to improve projects at Rerun.

The Staff Machine Learning Engineer will develop machine learning solutions for online gaming, drive initiatives, mentor engineers, and ensure project alignment with business goals.

As a Middle/Senior ML Engineer, you will create and improve ML models, collaborate with teams, maintain production models, and document processes.

Oversee ML projects, manage a team, design LLMs, implement AWS solutions, and ensure best practices in ML lifecycle and team development.

As a Senior Data Engineer, you'll design scalable data pipelines, collaborate with engineers and product teams, and evolve the architecture to support growth in users and data.

As a Senior DevOps/ML Infrastructure Engineer, you'll manage infrastructure, support ML model integration, and build automated MLOps pipelines in a collaborative setting.

As an ML Engineer, you will develop ML models, collaborate with teams, maintain model performance, and drive innovation in ML technologies.

As an ML Engineer at Provectus, you'll create and improve ML models, collaborate on production efforts, develop experimentation roadmaps, and maintain model performance.

As an ML Engineer, create and improve ML models, collaborate with teams, maintain experimentation pipelines, and stay updated with ML advancements.

The Machine Learning Platform Engineer will manage cloud infrastructure, support AI researchers, and deploy models in production, focusing on MLOps and CI/CD practices.