Top Machine Learning Jobs in Barcelona

Build and deploy production ML systems for large-scale ecommerce search and recommendations using text, image, and multimodal approaches. Tune and integrate LLMs and transformer models, develop end-to-end visual solutions, improve business KPIs through experimentation, and collaborate across teams to productize and scale ML capabilities.

The Independent Board Director will provide strategic guidance and insights on performance advertising technology, particularly related to DSP strategy, ML optimization, and advertiser growth.

Seeking an independent board director with expertise in ML-driven products and data platforms. The role focuses on guiding the company's data-driven culture and product strategies, not on day-to-day operations.

As an AI Product Manager, you'll shape the AI product roadmap, collaborate with cross-functional teams, and ensure AI technologies meet user needs and business objectives.

Lead the technical and product vision for the UA DSP, unifying Data Science, Data Engineering, Analytics, BI, and bidding/prediction backend. Own roadmap from bidding/prediction to reporting, manage and grow a ~20-person cross-functional team, partner with GTM and sales, and drive transition from managed-service to self-service advertiser tooling.

Build and scale MLOps infrastructure that moves machine learning models from development to production. Responsibilities include model serving, automated training and deployment, CI/CD, monitoring, drift detection, rollback mechanisms, streaming feature pipelines, and agentic workflow integration. The role requires collaboration with data science, platform, and product teams to deliver reliable, observable, low-latency ML systems.

Build and own pricing data science capabilities, including demand and elasticity models, forecasting, willingness-to-pay models, pricing optimization, experimentation, and causal analysis. Deploy and monitor machine learning systems, establish governed pricing metrics, and partner with Commercial, Finance, and Product to improve margin and revenue. Set analytical standards for pricing decisions and build reusable analytical capabilities.

Build and enhance RAG systems, AI components, backend services, data pipelines, and REST APIs under senior guidance. Write production code, tests, evaluation harnesses, documentation, and runbooks. Support AWS deployments using containers and CI/CD, investigate model failure modes, and contribute to architectural decisions. The role offers increasing ownership while collaborating with senior engineers, FDEs, FDXs, and enterprise clients in distributed teams.

Build core components of a diagnostic and personalization platform: backend data pipelines, frontends, services for genomic data ingestion, ML model integration, APIs, and cloud infrastructure. Collaborate with product and ML teams, iterate on prototypes and MVPs, and make architectural decisions supporting scalability and reliability.

Define and execute the product roadmap for AI-driven blockchain security monitoring tools. Collaborate with cross-functional teams, analyze market and customer feedback, deliver features on time, and communicate with stakeholders to align expectations and improve product offerings.

Lead architecture and hands-on implementation of scalable decision automation and production ML systems for Candy Crush Saga. Build reusable decisioning foundations, improve experimentation and causal inference tooling, mentor senior engineers, and ensure reliability, observability, and cross-team alignment for player-facing personalization and adaptation at scale.

Own Go-To-Market for performance media buyers: build relationships, close and onboard clients, represent Kayzen at industry events, advise prospects on product strategy, and funnel market feedback across teams.

Lead strategy and roadmap for BidMachines supply-side product. Own product lifecycle, collaborate with engineering, sales, publishers and data teams, analyze supply performance, and drive features for inventory management, auction dynamics, and demand-supply matching to maximize publisher revenue and advertiser satisfaction.

As an AI Director, lead AI and data programs for Specialty Chemicals, drive account growth, mentor teams, and engage C-level stakeholders strategically.

Drive innovation in post-training methodologies for AI models, focusing on agentic behaviors, tool use, and enhancing model capabilities for real-world applications.

As an AI Research Engineer, you'll optimize model deployment and inference architectures for AI systems, enhancing performance across various applications, especially on resource-constrained devices. Responsibilities include designing efficient serving architectures, conducting inference tests, and collaborating with teams to integrate solutions.

As an AI Research Engineer, you will develop and optimize vision-language models, managing the full model lifecycle from training to deployment, focusing on efficiency and innovation in multimodal architectures.

Lead Westernacher's Spain market by defining and executing market strategy, driving sales and profitability, and building client relationships. Split role between ~50% commercial leadership (business development, go-to-market, partner management) and ~50% delivery engagement (Project Director/Program Manager ensuring successful ERP/SAP transformations). Recruit and develop local team and ensure delivery and quality standards.

The Head of Education & Community at Siena is responsible for developing product education, onboarding programs, community events, and market education resources. This role involves creating curricula, conducting workshops, and supporting sales with training and demos while leveraging AI for teaching efficiency.

Design, build, deploy, and continuously improve production-grade machine learning systems for a proactive AI platform. Own projects end to end, including data curation, model training, evaluation, inference, monitoring, troubleshooting, and optimization. Translate research into reliable systems while balancing latency, cost, safety, and scalability. Collaborate with research, engineering, and product teams, mentor engineers, and drive complex initiatives independently.

Design, build, and operate scalable search, retrieval, and personalization systems. Develop ML models across candidate generation to ranking, leverage embeddings and LLMs, run A/B experiments, optimize for latency and scalability, and collaborate with product and data teams to deploy robust production ML services.

As a Senior Data Scientist at Back Market, you will design and implement machine learning models to optimize pricing strategies, collaborate with engineers, and communicate findings to stakeholders.

Lead and scale a Fraud Operations team to protect marketplace financial integrity. Own roadmap, KPIs, investigation standards, chargeback management, governance, workforce planning, and cross-functional partnership with Product, Data, Payments, and Finance to improve detection and reduce financial exposure.

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 role involves designing and developing model evaluation pipelines, user studies for subjective evaluations, and automated dashboards to report results, alongside leading the evaluation team and communicating with other teams to improve model performance.