Top Artificial Intelligence Jobs in Spain
As a Machine Learning Engineer at GitLab, you'll design and implement evaluators for LLM assessment, build scalable evaluation pipelines, manage datasets, and collaborate with other teams to ensure AI feature quality. Your role involves optimizing ML evaluation systems and aligning solutions with GitLab's infrastructure.
The Principal Data & AI Enterprise Architect leads the creation and implementation of data and AI strategies, aligning them with business objectives while ensuring scalability and security. This role involves collaboration with various teams to drive AI integration and oversee architectural design in AI/ML projects to enhance operational efficiency and customer experience.
The Principal Data & AI Enterprise Architect will define and design enterprise data and AI architecture, aligning initiatives with business goals. Responsibilities include leading AI and ML strategies, implementing frameworks, ensuring compliance, and collaborating with cross-functional teams to enhance operational efficiency through AI-driven solutions.
The Principal Data/AI Enterprise Architect will lead the design and implementation of data and AI architecture across the enterprise, ensuring alignment with business goals and focusing on scalability, security, and innovation. Responsibilities include developing data and AI strategies, overseeing AI/ML project frameworks, and collaborating with cross-functional teams to enhance operational efficiency and customer experience.
The Principal Data & AI Enterprise Architect is responsible for defining and driving the enterprise data and AI architecture, ensuring alignment with business goals. The role focuses on scalability, security, and innovation, collaborating with cross-functional teams to integrate AI solutions that enhance decision-making and operational efficiency.
The Senior Software Engineer will design and maintain production-level models to monitor datasets and engineering services, leveraging machine learning and AI techniques. Responsibilities include developing scalable API endpoints, mentoring junior team members, collaborating across teams, and identifying opportunities for innovation.
As a Principal AI Platform Architect at Disney, you'll lead the architectural vision for the Generative AI Platform, driving innovative solutions and ensuring scalability. Collaborate with multi-disciplinary teams to implement best practices, mentor developers, and adapt to emerging AI trends, all while enhancing guest experiences across Disney's digital landscape.
As a Senior Data Scientist in GM Motorsports, you will collaborate with cross-functional teams to develop analytics and predictive models using advanced machine learning and AI techniques. Your responsibilities include data preprocessing, model building, and presenting findings through data visualization, all aimed at enhancing race team performance and achieving competitive advantages.
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In this Senior Data Scientist role, you will collaborate with cross-functional teams to design, develop, and implement predictive models and machine learning algorithms. You will analyze data to derive insights, monitor model effectiveness, and create data visualizations to support GM Motorsports' strategic and analytics needs.
As a Principal Software Engineer, you'll enhance the robustness and scalability of Machine Learning infrastructure, optimizing Kubernetes and Kubeflow, troubleshooting HPC issues, and collaborating with cross-functional teams for effective solutions.
The Principal Software Engineer will architect and develop data ingestion and processing systems for AI applications, enhance data infrastructure, automate ETL processes, and mentor junior engineers while ensuring system reliability and scalability.
The Principal Software Engineer will design, develop, and maintain the AI/ML platform infrastructure while collaborating with data scientists and engineers. Key responsibilities include enhancing the scalability of model training, managing resource utilization, and developing tools for model versioning and experiment tracking.
The Director of AIDA R&D AI & Data Solutions Engineering will lead and manage a data solutions engineering team, focusing on the maturity and delivery of innovative data solutions. Responsibilities include project management, designing scalable solutions, ensuring compliance, and collaborating with business stakeholders to define project goals and deliverables.
The Director of Analytics Platform Delivery at Pfizer will manage the engineering, security, compliance, and operational oversight of key data and analytics technologies. They will lead a team of engineers, establish partnerships with external technology suppliers, and drive innovation in data and analytics practices.
The Chief Systems Engineer will lead systems engineering efforts for a Wargaming Program, guiding the transition of prototypes into production. Responsibilities include modeling systems of systems, risk management, talent assessment, and maintaining technology roadmaps, within a collaborative technical team.
The Generative AI Architect will design and execute a generative AI platform, influencing systems engineering and software architecture while ensuring technical approaches meet mission needs. This role includes leading collaborative efforts, integrating software components, and solving complex problems in the defense sector.
As a Software Engineer, you will develop and optimize interfaces for AI/ML tools, collaborate with cross-functional teams, design scalable solutions, and implement best practices in software development. Your role involves maintaining system performance, troubleshooting issues, and staying updated with AI/ML advancements.
As a Software Engineer focused on AI/ML interface development, you will design, develop, and maintain scalable interfaces that integrate AI tools with user-facing applications. Responsibilities include collaborating with teams to implement AI solutions, designing APIs, optimizing performance, and contributing to software development best practices.
As a Senior Software Architect, you'll lead software architecture design teams, enhance modeling and simulation capabilities, and influence stakeholders in modernizing workflows. Engage with users to refine requirements, mentor team members, and drive strategic planning for software development and analysis projects in support of space programs.
The Space Missions Systems Engineer will provide systems engineering support for space enterprise C3 systems, lead software test planning, improve ground systems, and influence future C2 investments, ensuring that systems and capabilities meet customer requirements and operate effectively.
As a Principal Solutions Engineer, you will engage with clients to understand their needs and design tailored solutions. Your role includes developing innovative solutions, providing technical leadership, communicating complex concepts, and coordinating cross-functional projects to enhance the data cloud platform.
The AI Center Technical Manager will lead a team of ML engineers, focusing on AI model deployment and operationalization. Responsibilities include developing frameworks for AI operations, overseeing the deployment of ML solutions, ensuring code quality through DevSecOps, and collaborating with data engineers and scientists. The role requires hands-on coding and leadership to foster team growth and innovative AI practices.
The Principal Software Engineer will lead the design and implementation of data ingestion and management systems for the AI platform. Responsibilities include developing scalable data platforms, automating ETL processes, and mentoring junior team members while enhancing developer productivity.
As an Applied AI Scientist at ZS, you will develop advanced algorithms, execute statistical techniques on large datasets, evaluate emerging technologies, and contribute to the firm's thought leadership by researching and publishing on evolving topics.
As a Senior Software Engineer on the AI team at Clay, you will develop LLM-driven applications, enhance AI capabilities, and manage production AI/ML systems across the product lifecycle. You will work on building tools to monitor model performance and address user needs effectively.
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