Top Python Jobs in Dublin

The Cloud Software Engineer will design and maintain scalable cloud infrastructure, manage infrastructure as code, optimize CI/CD pipelines, and ensure high availability of services.

The Data Analyst, Growth will analyze marketing data to deliver actionable insights, design dashboards, automate reporting, and support cross-functional projects to improve client acquisition and retention.

As a Senior Backend Engineer, you'll develop features using Python and various AWS services, focusing on AI-driven solutions for the insurance sector.

Lead the Applied AI Team in developing and deploying ML systems for clinical care, mentoring engineers, and driving initiatives across the AI stack.

The AI/ML Engineer will develop and implement ML systems for secure-code understanding, manage infrastructure for LLMs, optimize models, and conduct research.

The role involves engineering, testing, and the development of advanced frontend components for an AI-driven cybersecurity product, integrating AI features and ensuring best practices are followed.

The Fullstack Engineer will focus on product software engineering, agents framework engineering, and R&D in AI and cybersecurity. Responsibilities include hands-on engineering, testing, and integrating AI Agents into existing systems.

The Fullstack Engineer will focus on DevOps, designing infrastructure and deployment pipelines, and collaborating on AI Agent features and cybersecurity solutions.

As a Software Engineering Intern, you will build scalable solutions, write production-ready code, and work with interdisciplinary teams.

The Automation Test Engineer will design and develop AI-driven automated testing frameworks, mentor junior engineers, and ensure software quality through test automation and machine learning techniques.

The Staff Machine Learning Scientist will lead ML projects, mentor engineers, define new features, conduct research, and collaborate with product teams to deliver impactful ML products.

Design and maintain data infrastructure, build pipelines for data collection, ensure data quality, and collaborate with stakeholders on data requirements.