Top Machine Learning Jobs in Barcelona

Design, build, and own scalable backend services, APIs, and high-performance web frontends for an autonomous procurement platform. Improve reliability, security, and performance, implement async task pipelines, and collaborate with product and design. Mentor juniors, participate in code reviews, and leverage AI-assisted tools while shipping iteratively in a globally distributed, async-first team.

Lead and develop a team of Data Scientists and ML Engineers building production machine-learning systems for logistics. Drive AI adoption, roadmap prioritization, agile execution, and measurable business outcomes. Partner with Product Managers, Staff ML Engineers, and the MLOps platform team to deploy scalable solutions. The role requires deep hands-on experience with production ML, recommender systems, pricing algorithms, statistical models, and modern data and AI technologies, alongside strong people leadership and executive communication skills.

Design, build, validate, deploy, and monitor predictive lifetime value (pLTV) models for subscription products. Partner with data engineering and cross-functional teams to integrate models into production, run experiments (A/B tests), troubleshoot anomalies, and translate insights into actionable recommendations while adopting best-practice ML techniques.

The role involves developing and optimizing electrochemical measurement methods, mathematical modeling, algorithm development, and leading system validation for diagnostic technologies.

Own the technical roadmap for Veriff’s physical document identity verification product, balancing accuracy, coverage, fraud detection, conversion, latency, and cost. Partner with ML engineers, data scientists, operations, annotation teams, analytics, legal, marketing, and go-to-market teams. Lead technical customer discussions, define model success metrics, investigate data issues, manage trade-offs, and launch scalable product improvements.

Lead the strategy, development, deployment, and scaling of AI-powered health products across governments and public health systems in the Global South. Own product roadmaps, execution, stakeholder adoption, partnerships, grant development, and portfolio expansion. Collaborate with engineering, data science, government, donor, and implementation teams to embed sustainable, measurable AI solutions across Africa and Southeast Asia.

Lead the strategy, design, deployment, and scale-up of AI-powered health products across the Global South. Own product roadmaps, execution, government-system integration, stakeholder adoption, partnerships, grant development, and portfolio expansion. Collaborate with engineering, machine learning, program, and domain teams to deliver sustainable, measurable public-health impact.

Lead procurement digitalization by developing strategy and roadmap, assessing technologies (AI/ML/RPA), advising stakeholders, driving AI initiatives, improving processes, and ensuring adoption and ROI across global procurement.

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.

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 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.

Translate business problems into analytical approaches; analyze structured and unstructured data; build and maintain ETL/ELT pipelines and scalable data-processing solutions; perform data-quality checks and optimization; develop automation and analytical solutions using SQL, Python or Scala; support reporting, advanced analytics and ML use cases; collaborate with cross-functional teams and communicate findings to technical and non-technical stakeholders while managing multiple client deliverables.

Responsible for driving strategy and execution of marketplace features, optimizing the partner experience, collaborating cross-functionally, and prioritizing projects that align with business goals.

Lead and build Solidgate's ML/AI function from scratch: define vision and architecture, hire and lead the team, deliver real-time decisioning and recommendation systems, partner with Product/Engineering/Data Platform, run experiments and A/B tests, and translate models into revenue-driving production features.

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.

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

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.

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.

Design and deliver innovative, user-centric cross-platform experiences affecting millions of customers. Partner with design, PMs and engineers to build high-quality, measurable UX, leverage customer insights, A/B testing and personalization, balance quality with MVP testing strategies, and drive cross-functional collaboration.

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.

Lead high-complexity data science initiatives improving search ranking, retrieval, relevance, and evaluation. Develop and deploy production machine-learning and NLP solutions, investigate LLM-based ranking features, optimize SQL queries, and work with sparse privacy-preserving data. Define strategies for ambiguous problems, guide other data scientists, collaborate with product teams, and own projects from scoping through production.

Seeking Quantitative Finance Experts to train and evaluate AI models by assessing accuracy, reviewing responses, and providing domain-specific feedback. Requires expertise in Quantitative Finance and strong analytical skills.

Research and investigate global fraud trends using BioCatch data and external sources. Produce data-driven insights, visualizations, written thought leadership, dashboards, and presentations. Build repositories and automate analysis workflows while applying fraud expertise and AI tools to validate findings and support sales and marketing.

Lead statistical strategy and delivery for Phase I-IV clinical trials embedded with a pharmaceutical sponsor. Design analyses, support protocol and reporting activities, oversee programming/CRO work, apply SAS/R (R Shiny)/Python and ML/DL methods for analyses and automation, and mentor junior statisticians.