Top Machine Learning Jobs in Spain

Architect and build the AI layer for Neo4j’s Hume Maestro platform. Responsibilities include setting the AI technical roadmap, contributing hands-on to production code, designing scalable AI architectures, establishing model evaluation and deployment practices, integrating AI with front-end and platform systems, and collaborating with Product and Science stakeholders. The role may eventually evolve into leading and mentoring a dedicated AI engineering team.

Lead discovery, design and delivery of Big Data and AI products for internal Kyivstar teams. Engage stakeholders, define vision, prioritize roadmaps, manage PoCs/MVPs to production, coordinate data and engineering teams, run pilots and measure business impact to ensure solutions create measurable value.

Develop and own production-ready machine learning, LLM, NLP, and RAG solutions within Palantir Foundry and AIP. Responsibilities include data exploration, model development, evaluation, deployment, monitoring, workflow integration, and optimization for accuracy, scalability, reliability, latency, and cost. Collaborate with engineers and business stakeholders, make architecture decisions, translate business needs into AI solutions, and communicate model behavior and limitations.

As a Fraud Data Analyst, you will architect real-time defense strategies against payment fraud, develop precision rules, optimize decisioning stacks, and report performance metrics to senior leadership while ensuring a frictionless user experience.

Own full-cycle recruiting for technical roles, partner with hiring managers to define roles, source and close candidates, build scalable systems and pipelines, optimize hiring with data, and support a global, remote people team while acting as a culture ambassador.

Lead legal counsel for an adtech company providing commercial, product, privacy, and regulatory counsel. Negotiate complex agreements, advise on global privacy and IAB standards, support product launches and AI use cases, manage data governance and incident response, oversee corporate compliance and outside counsel, and build scalable legal operations and contract workflows.

Serve as the bridge between engineering and business to deliver AI products from PoC to production. Translate business needs into product requirements, manage planning and prioritization, challenge technical decisions for scalability, mitigate risks and dependencies, and maintain stakeholder alignment and delivery cadence across cross-functional teams.

The Principal Product Manager will drive the strategy for AI-based pricing and reconciliation across travel services, manage model lifecycles, and ensure operational integrity in real-time financial data processing in collaboration with cross-functional teams.

Lead strategy and execution for creative products, define requirements and success metrics, prioritize with engineering and design, run experiments, collaborate cross-functionally, and drive product vision to improve creative automation, optimisation and measurement across mobile and CTV.

Lead a cross-functional team building ML-powered marketplace catalogue systems, including LLM enrichment, categorization, translation, moderation, embeddings, recommendations, and evaluation infrastructure. Own the product data pipeline, ML roadmap, quality SLAs, experimentation, reliability, technical debt, and incident response. Define OKRs, lead cross-team initiatives, hire and develop engineers, and connect catalogue quality improvements to conversion, discovery, and merchant growth.

Designs and delivers production conversational AI systems, including multi-turn agents, LLM reasoning loops, and multi-agent orchestration. Leads end-to-end AI initiatives using Python, Azure, MLflow, and Databricks; benchmarks and maintains models; mentors junior staff; leads cross-functional teams; and partners with customers to develop solutions for complex enterprise domains.

Develop, deploy, and optimize machine learning and AI solutions, including multi-agent systems, RAG applications, LLM integrations, and agentic workflows. Evaluate and improve model performance, prompts, and AI reliability for production use. Collaborate with platform teams, data engineers, data scientists, and stakeholders while contributing to coding, testing, debugging, and code reviews across the development lifecycle.

Join the Digital Innovation Team at Airbus to develop AI and machine learning models for business improvements using advanced analytics. Collaborate and communicate findings effectively while staying updated on technological advancements.

Conduct advanced AI/ML research for drug discovery and therapeutic design, developing foundation models, generative models, and representation learning methods for biological sequences. Integrate AI-guided design with wet-lab validation, analyze complex biological datasets, collaborate across computational and experimental teams, communicate findings, maintain code repositories, and publish research in leading conferences and journals.

The Data Scientist will design algorithms for insights, structure data, collaborate with machine learning engineers, and analyze datasets to improve workflow automation and product value.

Join Vizzuality's talent pool to contribute to sustainability efforts through science, data, design, and project management roles. Apply with your CV and cover letter to be considered when vacancies arise.

Design scalable, secure enterprise architectures for Generative AI and ML solutions, validate technical feasibility via POCs, define production-ready model and inference patterns, ensure alignment with security, governance and cost targets, and provide technical leadership and reusable architecture patterns across teams.

Design scalable, secure enterprise architectures for Generative AI and ML solutions, validate technical feasibility via prototypes/POCs, define production-ready model requirements and scaling strategies, ensure alignment with governance/security, provide technical leadership and reusable architecture patterns, and evaluate/validate models and emerging AI technologies.

The Applied Scientist will solve impactful problems using deep learning models and statistical analysis, translating commercial goals into technical solutions.

As an AI Product Manager, you will lead the AI product development lifecycle, collaborate with teams, and align AI technologies with user needs.

Corti is seeking passionate individuals to join their talent community, shaping the future of healthcare through AI technologies. Opportunities include roles in AI technology, machine learning, and software development, focusing on reducing errors and improving patient outcomes.

The AI R&D & Effectiveness Lead will evaluate AI investments, build production-grade AI solutions, and manage AI capabilities to enhance Smadex's operational efficiency.

Lead Data, Analytics, AI, and GenAI presales activities for strategic enterprise opportunities. Facilitate discovery workshops, translate business needs into scalable architectures, lead RFP and RFI responses, and present solutions to executives. Design end-to-end AI and cloud architectures across Azure, GCP, Databricks, and open-source ecosystems. Advise on AI transformation use cases, roadmaps, governance, and implementation, while mentoring delivery teams and developing reusable frameworks, offerings, thought leadership, and customer success materials.

Build Solidgate’s new ML/AI function, developing production machine learning models, recommendation systems, and real-time transaction-routing decision systems. Own experimentation from ideation through A/B testing and deployment, engineer features from high-cardinality transactional data, integrate emerging AI technologies, and collaborate with Product, Engineering, and Data Platform teams on training and analytics pipelines.

Drive data science initiatives from opportunity identification through production deployment and monitoring. Partner with Product, Engineering, Sales, and Marketing stakeholders to deliver measurable business outcomes, selecting pragmatic solutions ranging from heuristics to advanced machine learning. Build scalable analytics and ML models, establish best practices, and translate technical findings into actionable business insights.