Top AI Jobs in Dublin

Design and demonstrate networking solutions, build and configure test topologies, collaborate with engineers, create reports, and improve product offerings.

The AI First Developer will deliver high-quality product features using AI across the development lifecycle, optimizing workflows and mentoring others in AI-driven engineering principles.

Senior Software Engineers at Mastercard design and code AI and cloud platforms, develop scalable software solutions, and mentor junior team members while collaborating with stakeholders.

As an Intermediate Backend Engineer, you'll enhance GitLab's AI capabilities using Ruby on Rails and Python, collaborating with other teams to improve the product and generate innovative solutions.

As a Full Stack Engineer AI, you will bridge machine learning and software engineering to create AI-powered financial services, developing full-stack applications, APIs, and user interfaces.

As a Full Stack AI Engineer, you'll integrate ML models with software engineering, building full-stack applications and collaborating across product and engineering teams.

Design and develop AI-driven solutions, mentor junior engineers, and lead complex projects in a staff software engineering role primarily using Python.

Develop and manage AI reliability infrastructure, implement monitoring systems, lead incident response, and optimize AI infrastructure performance.

As a Data Engineer on the ZAP team, you will design scalable data models, develop ELT pipelines, and optimize data delivery systems to enhance CRM insights.

Develop dynamic user interfaces for AI systems, focusing on responsive design, real-time data visualization, and collaboration with AI engineering teams.

The Staff Software Engineer will design and develop AI-driven solutions using Python and Azure AI services, provide technical leadership, mentor juniors, and integrate Generative AI models.

Skedda seeks a Senior AI Full-Stack Software Engineer to develop AI-powered features, implement test automation, and manage projects from concept to launch.

Develop and optimize low-level kernels for AI inference, improve inference engines, debug performance issues, and collaborate across teams.

The Principal Software Engineer (Full Stack) will lead the Evisort AI team in building AI-driven contract management solutions while collaborating with cross-functional teams and mentoring other engineers.

As a Staff AI QA Engineer at Kaseya, you'll craft testing strategies for AI platforms, validate AI behavior, and ensure data integrity, while collaborating with cross-functional teams.

As a Staff AI DevOps Engineer, you will build automated CI/CD frameworks, manage Kubernetes infrastructure, integrate MLOps practices, and enforce security protocols to enhance AI platform efficiency.

As a Staff AI QA Engineer, you'll design testing strategies and automation frameworks for AI platforms, validate AI behavior, and ensure data quality across integrations.

As a Staff AI DevOps Engineer, you will design CI/CD pipelines, implement IaC, manage Kubernetes infrastructure, and optimize cloud environments for AI workloads.

Join Welo Data's global contributor network to work on flexible, remote AI projects such as annotation, evaluation, and prompt creation, requiring Albanian fluency.

As an LLM Engineer, you will optimize large language models for user interactions, oversee algorithm development, manage datasets, and enhance product features.

Lead the Reliability Engineering team to enhance reliability metrics for AI products while managing large-scale model serving and training systems. Drive the development of comprehensive monitoring, automated recovery systems, and incident response processes, aligning efforts with company goals and fostering a culture of reliability and innovation.

The Product Engineer will build internal tools and applications using AI and automation to enhance productivity at Kota, working cross-functionally.

Join Telnyx as a Python Engineer to develop AI applications, APIs, and microservices focusing on performance and scalability, while integrating cutting-edge AI technologies.

The role involves optimizing large scale AI/HPC networks, developing performance metrics, and enhancing infrastructure while engaging in significant travel for buildouts.

The role involves managing large-scale unstructured data for ML systems, contributing to the entire product lifecycle, and building reliable system software.