Top Machine Learning Jobs in Spain

Leads global early-asset forecasting, commercial market insights, and business-development investment analysis across respiratory and immunology portfolios. Builds patient-based models, scenarios, and risk-adjusted forecasts; supports licensing, partnerships, and acquisitions; advises executives on portfolio and deal decisions; oversees market research; and advances responsible AI, automation, and model governance.

Supports Account Executives throughout the sales cycle by leading technical discovery, solution design, demonstrations, workshops, proofs of concept, evaluations, and technical validation. Translates engineering, simulation, HPC, AI, and infrastructure requirements into Rescale recommendations, documents opportunities in Salesforce, resolves technical risks, supports negotiations, and ensures effective post-sale handoffs across Northern Europe.

Lead the design and delivery of scalable, cloud-based data architectures across SGS. Define data governance, standards, and enterprise models; translate business needs into batch and real-time solutions; and lead architecture for data projects. Collaborate with global stakeholders, cloud partners, and delivery teams while supporting hands-on implementation, proof-of-concepts, platform adoption, documentation, and emerging technology evaluation.

Lead Adwake’s B2B marketing strategy across brand positioning, sales enablement, content, events, demand generation, and digital campaigns. Manage and mentor a lean marketing team, collaborate with sales on collateral and outbound initiatives, oversee industry activations, develop thought-leadership content, and track campaign, event, budget, and team performance metrics. Experience in digital advertising, adtech, mobile applications, gaming, or app growth is beneficial.

Lead Jampp’s transition to deep learning and embedding-based architectures for large-scale, latency-sensitive programmatic advertising. Design, deploy, and optimize neural network models for bidding, ranking, prediction, and campaign optimization. Establish modeling and production standards, guide architecture and infrastructure decisions, mentor data scientists, and collaborate with engineering teams to build scalable training, serving, and feedback systems.

Review and annotate images by identifying people, actions, and predefined categories. Follow detailed annotation guidelines, maintain accuracy and consistency, review completed work, and help create high-quality datasets for AI models. The role requires strong attention to detail, independent work, reliability, and EU citizenship with residence in the European Union.

Develop and enhance electronic trading capabilities for commodity products. Analyze trading, client, and market data; build APIs, automation, pricing, risk-monitoring, and trading analytics tools; and improve eTrading platforms and workflows. Collaborate with Sales, Structuring, Quantitative, and Technology teams to expand digital client services, optimize risk controls, improve efficiency, and support scalable business growth.

Design, develop, evaluate, and deploy deep learning and embedding-based models for real-time advertising prediction, bidding, and optimization. Work with massive, high-cardinality datasets, machine learning pipelines, feature infrastructure, and production model monitoring. Collaborate with data scientists, ML engineers, software engineers, and data engineers to translate experiments into scalable solutions and measure their impact on campaigns and business outcomes.

Develops and maintains sophisticated distributed web applications using Python, AWS, APIs, and modern cloud technologies. Designs system solutions, fixes complex bugs, performs advanced refactoring, participates in code reviews and system design, and ensures quality API documentation. Collaborates with product and analytics teams, follows Agile and CI/CD practices, mentors junior engineers, contributes to technical documentation, and may lead projects or supervise team members.

Lead the Agentic Discovery product chapter, initially owning business tooling, dashboards, transparency, and controls for AI-powered commerce experiences. Define strategy, align ML, engineering, design, and go-to-market teams, scale experimentation, launch reliable LLM-powered experiences, and establish metrics tied to usage, conversion, revenue, and engagement. The role will expand to chapter-wide leadership across on-site, offsite, and integrated agentic discovery surfaces.

Designs, builds, and evaluates research prototypes and production-ready systems for portable AI agents, model routing, provider interoperability, memory, retrieval, tool use, and multi-agent workflows. Responsibilities include developing evaluation frameworks, conducting statistically rigorous experiments, creating schemas and APIs, optimizing model and agent systems, and translating research into secure, reliable, reusable components. The role collaborates across research, infrastructure, security, product, and engineering teams and communicates findings through technical reports, benchmarks, demonstrations, open-source releases, and publications.

Design, build, and maintain production SaaS products that transform public web data into market intelligence. Develop AI- and LLM-based capabilities, modernize legacy systems toward scalable event-driven architectures, and work with distributed systems, cloud infrastructure, and domain-oriented design. Own projects from discovery through continuous improvement, collaborate across technical and customer-facing teams, improve engineering practices, and mentor less experienced engineers.

Lead end-to-end technical strategy for customer accounts, design scalable data and AI architectures, guide production deployments, drive Databricks adoption, and advise senior technical stakeholders. The role requires strong Python and SQL coding, distributed data systems expertise, public cloud experience, architecture leadership, customer-facing communication, and fluency in English and Portuguese.

Develop new business and revenue from banking and financial-services accounts in Spain. Manage strategic account plans, complex sales opportunities, partnerships, forecasting, pipeline, and deal closure. Collaborate with business development, sales engineering, account management, and executive leadership to drive technology adoption, customer success, and revenue growth. Represent the company at relevant events and communicate business value to senior and C-level stakeholders.

Designs, builds, and operates production-grade agentic AI systems and orchestration frameworks. Responsibilities include prompt architecture, tool and API integrations, monitoring, evaluation, cost controls, reliability improvements, and governance documentation. The engineer collaborates with data science, data engineering, and governance teams to ensure reliable, compliant workflows using structured healthcare and pharmaceutical data.

Six-month part-time curricular internship for final-year Engineering or IT students completing a Bachelor's final project. The student will support Airbus initiatives involving Industry 4.0, connected systems, machine learning, data analysis, or digital twins. Candidates need B2-level English, analytical and problem-solving abilities, communication skills, teamwork, and the ability to work in an international environment.

Interns on Oliver Wyman’s Data & Analytics team will design analytical solutions, develop and validate machine learning prototypes, model financial risk, analyze client data, and communicate findings to clients and colleagues. Projects may involve NLP, GenAI, customer churn, decarbonization, promotions, credit risk, and supply chain analytics. The role offers coaching, international collaboration, and exposure to consulting engagements across multiple industries.

Own product vision, strategy, roadmap, requirements, and end-to-end lifecycle coordination. Collaborate with developers, data scientists, researchers, business development, and customer success teams. Analyze product usage, report on KPIs, document user stories and release notes, track OKRs, and assess competitors and market trends in sustainability and financial investment.

Lead end-to-end process analysis using process mining and analytics to identify inefficiencies and automation opportunities. Translate business needs into actionable use cases, build process semantics and data foundations, implement scalable solutions, and promote adoption of Process Intelligence and AI-driven automation across functions.

AI/ML Engineers will build and deploy AI-native products, autonomous agents, LLM applications, RAG systems, and production ML pipelines. Responsibilities may include integrating AI into crypto infrastructure and consumer products, fine-tuning and evaluating models, optimizing inference, and developing agentic workflows and machine-to-machine payment systems. Engineers will work end-to-end with high-ownership teams in fast-moving environments.

Own the full enterprise customer journey from kickoff through adoption and ongoing value realization. Build executive and technical stakeholder relationships, lead QBRs and EBRs, translate product performance into business outcomes, manage risks and escalations, provide strategic ecommerce recommendations, maintain success plans, and partner with Account Management on retention and expansion.

Own enterprise customer relationships from kickoff through adoption and ongoing value realization. Lead success plans, QBRs, executive conversations, escalations, stakeholder alignment, training, and strategic recommendations. Translate technical capabilities and performance data into business outcomes such as revenue, conversion, and customer experience. Partner with Account Management to support retention and expansion while improving scalable onboarding and support processes.

Supports data collection, cleansing, exploratory analysis, predictive modeling, reporting, visualization, documentation, and data science innovation projects. Collaborates with Data Scientists and business stakeholders to generate insights and support data-driven decisions. The role is based in Sant Joan Despí, Spain, within Global Demand Planning, and reports to the Global Forecast Analyst Manager.

Lead and mentor a data science team building ML and LLM solutions for cybersecurity. Translate business needs into research and production ML objectives, prioritize roadmaps, collaborate cross-functionally, and drive technical vision, model development, and operationalization for malware detection and threat analysis.

Lead end-to-end ML product roadmaps and initiatives (e.g., Attachment Matcher, Transaction Categorizer). Collaborate with data scientists, engineers, and stakeholders to define, deliver, and monitor ML solutions that drive measurable business value for SMEs across Qonto's platform.