Top Machine Learning Jobs in Spain

Performs daily and monthly investment performance calculations and multi-level attribution across equity, fixed-income, and multi-asset portfolios. Analyzes alpha, allocation, selection, factor contributions, and risk-adjusted returns; investigates data issues and calculation breaks; ensures GIPS compliance; maintains controls and documentation; and partners with investment, client, technology, and data teams. Supports automation, AI, machine learning, and advanced analytics initiatives for performance measurement and exception management.

Performs daily and monthly investment performance calculations and multi-level attribution across equity, fixed income, and multi-asset portfolios. Analyzes alpha, allocation, selection, factor contributions, and risk-adjusted returns; partners with portfolio managers and client teams to explain results and resolve issues. Maintains GIPS-compliant procedures, controls, and documentation, investigates data and calculation breaks, and drives process improvements. Also develops controlled AI, automation, and advanced analytics use cases for performance measurement and exception management.

Drive business development and close high-value enterprise deals with global biotech and biopharma accounts across Europe. Own strategic customer relationships, deliver recurring revenue, partner with technical and customer success teams on complex proposals, provide market insights for product direction, build industry credibility, and improve enterprise sales processes and playbooks.

Conduct advanced research in artificial intelligence and machine learning, including deep learning, graphical models, reinforcement learning, computer perception, natural language processing, and data representation. Define complex business problems, design and deliver modeling solutions, evaluate model performance, establish scientific and engineering specifications, and build analytical roadmaps. Assess production implementation requirements, improve data capture methods, apply statistical and mathematical techniques, and resolve root causes and process bottlenecks.

Lead product vision and discovery for a genomics-driven diagnostic and personalization platform. Validate hypotheses with patients, clinicians, and partners; translate research into product specs; coordinate labs and data providers; partner with engineers and researchers to build AI prototypes; shape data, regulatory, and GTM strategy while making core product and architectural decisions.

Own the end-to-end lifecycle of production AI, machine learning, and GenAI products across banking operations, fraud, AML, growth, and marketing. Define roadmaps, evaluate models, guide deployment and monitoring, and partner with data scientists and engineers on scalable architectures. Establish standards and self-service tools for safe AI adoption while balancing innovation with security, privacy, compliance, reliability, and auditability in a regulated financial environment.

Own delivery of applied machine learning products from discovery through deployment. Translate operational challenges into technical requirements, coordinate data scientists, ML engineers, and stakeholders, and manage squad backlogs. Focus on automation, document verification, fraud detection, model monitoring, and continuous optimization. Evaluate model performance using metrics such as precision, recall, and F1 score while ensuring security, compliance, and data privacy standards in a regulated banking environment.

Analyze large-scale player data using Python and SQL, engineer features, and develop machine learning models and prediction pipelines to improve game revenue. Conduct experimental design, causal inference, and A/B testing, then present actionable findings to non-technical game teams. The role involves collaborating with global data and game development teams and delivering projects from exploratory analysis through deployed models.

Develop enterprise search and information retrieval solutions using generative AI, LLMs, RAG, agentic architectures, machine learning, and vector databases. Responsibilities include model development and evaluation, prompt engineering, search relevance tuning, data pipelines, embeddings, MLOps, API integration, experimentation, and stakeholder consulting. The role also leads proof-of-value projects, supports data-driven decisions, and improves scalable search systems.

Join the Orbit 12-month graduate program as an Associate Applied AI Engineer supporting customer engagements: uncover business challenges, prototype ML and LLM solutions on the Celonis Process Intelligence Platform, deliver proof projects and executive presentations, drive value realization, collaborate with product and engineering, and travel to meet clients.

The AI Engineer will build data pipelines and improve ML systems for reliability in production. Responsibilities include schema design, data infrastructure, and model evaluation, ensuring high-quality outputs and integration with product workflows.

Leads global early-asset forecasting, market insights, commercial diligence, and investment-case development across respiratory and immunology portfolios. Builds patient-based models, evaluates licensing and acquisition opportunities, advises executives, oversees market research, and supports therapeutic-area strategy. The role also advances responsible AI, predictive analytics, automation, and model governance to improve decision quality and portfolio prioritization.

Advise clients on becoming data-driven by assessing data and ML maturity, identifying use cases, and defining implementation roadmaps. Collaborate with data scientists, engineers, and architects on AI solutions, governance, MLOps, and analytics centers of excellence. Support business development, client relationships, conferences, sales meetings, thought leadership, and the growth of the Data & AI consulting practice.

Provides strategic and hands-on biostatistical leadership across pharmaceutical discovery, translational, biomarker, and early research programs. Designs studies, analyzes complex biological datasets, develops advanced statistical methods and reproducible R workflows, and translates evidence into portfolio decisions. The role collaborates with quantitative and scientific functions, supports publications and external partnerships, mentors statisticians, and advances data-driven analytical practices.

Leads clinical data science delivery and team development, designing advanced statistical models and machine learning methods for clinical research. Oversees data analysis, management, regulatory compliance, and trial optimization while collaborating with clinical, biostatistical, and regulatory teams. Communicates complex insights to senior stakeholders and external partners and drives innovation across clinical development programs.

Drives technical pre-sales success for large and strategic fleet opportunities through discovery, demonstrations, pilots, and proof-of-concepts. Assesses customer challenges, designs suitable solutions, supports partners and channel teams, and collaborates with sales, product, and customer teams to grow revenue. The role also develops segment expertise, leads strategic implementation projects, contributes product feedback, documents opportunities in JIRA and Salesforce, and mentors other Solutions Engineers.

Join Celonis's 12-month Orbit graduate program as an Associate Applied AI Engineer (Value Engineer). Support DACH customer engagements, prototype ML and LLM-based AI solutions on the Celonis Process Intelligence Platform, quantify business value, present to executives, drive change management, and collaborate with product and engineering to scale reusable AI solutions.

Analyze large-scale mobile user and app datasets to generate insights for Product and Machine Learning strategies. Collaborate with business and technical teams to improve platform and campaign performance, develop dashboards and data-driven processes, conduct statistical analyses and hypothesis testing, and communicate recommendations to stakeholders.

Own end-to-end talent acquisition and headhunting for Arago’s technical hiring across France, North America, and Israel. Partner with the CEO, CTOs, and engineering leaders to define roles, source and close senior engineers, scientists, and technical leaders across hardware, optical, software, and research. Build proactive sourcing pipelines, improve interview processes and hiring standards, monitor pipeline health and hiring velocity, and communicate progress to leadership.

Identifies, designs, deploys, and sustains AI solutions within a Wind Engineering subsystem. Partners with engineering leaders to prioritize use cases, integrates AI into engineering workflows, ensures governance and cybersecurity compliance, drives adoption, and monitors solution performance and value. The role develops applications, agentic workflows, copilots, automation, predictive models, and knowledge systems while contributing reusable patterns and innovations to the broader AI community.

Leads the identification, design, deployment, integration, governance, adoption, and continuous improvement of AI solutions across a Wind Engineering subsystem. Partners with engineering and business leaders to prioritize AI use cases, build roadmaps, configure AI applications and agentic workflows, integrate solutions into engineering processes, validate outputs, ensure security and responsible AI compliance, educate teams, and monitor solution performance and business value.

Lead data strategy and advanced analytics for the Marketplace. Design experiments, apply statistical and machine learning methods, build scalable data products, and translate insights into recommendations affecting conversion, retention, revenue, and ROI. Partner with Product, Engineering, Marketing, Sales, and business stakeholders, prioritize analytical work, improve tracking, and mentor team members.

Design, develop, simulate, test, and deploy intelligent robotic systems across virtual and physical environments. Build digital twins, perception systems, navigation and control algorithms, and sim-to-real workflows using robotics, AI, computer vision, and reinforcement learning. Collaborate with research and engineering teams to prototype emerging technologies and deliver production-ready autonomous robotic solutions.

Leads cybersecurity and technology risk for Santander’s Data & AI division. Advises executives on cyber risk, resilience, security investments, and security posture; oversees governance, regulatory compliance, controls, reporting, audits, and remediation. Partners with Risk, Compliance, Legal, Audit, Privacy, Technology, and business stakeholders. Ensures security-by-design, critical data protection, threat mitigation, and secure, responsible deployment of AI capabilities in alignment with group strategy and regulatory expectations.

Own Afori’s machine-learning reasoning systems for insurance agents. Responsibilities include designing continuous-learning loops, fine-tuning and distilling open-weight and proprietary LLMs for German insurance NLP, building cross-sell intelligence models, and establishing evaluation standards, benchmarks, abstention checks, faithfulness checks, and production serving infrastructure. The role requires shipping cost-effective ML systems at scale in a regulated, early-stage environment.