Top Machine Learning Jobs in Spain

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.

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.

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 Senior Machine Learning Engineer, you will develop and scale customer-facing AI models, ensuring quality integration with business solutions, and mentoring peers.

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

The Senior Data Scientist drives AI platform development, establishes standards, partners with engineering teams, mentors, and ensures responsible AI adoption across Awin.

Lead the development of robot policies and task planning. Collaborate with cross-functional teams to create real-world robotics solutions, incorporating AI technologies and MLOps practices.

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

The Senior Machine Learning Engineer will design evaluation frameworks, diagnose model performance, develop ML systems, and mentor junior engineers while collaborating across teams.

Lead the development of high-fidelity simulations and validation workflows for robotic systems, focusing on sensor simulation and mechanical modeling to ensure reliable performance in real-world and virtual environments.

Design and build simulation environments for robotics research, implement RL algorithms, and evaluate policies for stability and transfer potential. Collaborate with teams and document results.

As a Machine Learning Engineer, you will build and scale ML infrastructure, manage deployments, and optimize models for production, collaborating with researchers and engineers.

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 development of AI/ML systems for real-time applications across various industries. Responsibilities include data analysis, system architecture, developing models, mentoring, and collaborating with engineers.

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

You will analyze model behavior in a live auction environment, propose enhancements, and collaborate on performance monitoring tooling.

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.

The Senior Machine Learning Engineer will build scalable AI tools, collaborate with cross-functional teams, and optimize AI pipelines using cloud resources. The role involves mentorship and development of ML infrastructure.

The ML Ops Engineer will build and operate scalable ML inference platforms, focusing on model serving infrastructure and deployment pipelines for AI applications.

The role involves developing and supporting data processing pipelines, collaborating with ML Engineers, and improving infrastructure while mentoring team members.

As an AI/ML Engineer at Air Apps, you'll design and optimize machine learning models for mobile applications, collaborate with teams, and innovate enhancements through AI-driven solutions.

This role involves developing and training advanced machine learning models in a collaborative environment, focusing on biomedical research applications, particularly in drug discovery processes.

As an ML Researcher, you will design evaluation frameworks, manage evaluation infrastructure, and track model performance through internal and external benchmarks.