Top Machine Learning Jobs in Dublin

Develop and implement machine learning models to improve user targeting and personalization, analyze data, collaborate with teams, and conduct A/B tests to optimize growth initiatives.

The Applied Scientist will solve impactful problems using deep learning models and statistical analysis, translating commercial goals into technical solutions.

The role involves developing and optimizing machine learning models, analyzing large datasets, and collaborating with teams to enhance fraud detection and risk decisioning.

As a Staff Machine Learning Engineer, you'll lead ML model development, optimize data pipelines, mentor junior engineers, and enhance fraud detection for PayPal's risk decision-making.

The Principal Software Engineer will create high-performance AI/ML applications, optimize inference techniques, contribute to open-source projects, and lead coordination across engineering teams.

As a Principal Machine Learning Engineer, you will drive high-impact AI product development, lead exploratory data analysis, and collaborate within cross-functional teams to deliver innovative solutions.

The Senior Machine Learning Engineer will leverage AI to optimize Workday implementations, requiring 8+ years of software engineering experience and expertise in Python and other programming languages.

Lead a team of machine learning engineers and optimization specialists to develop decision systems for monetization strategies, ensuring scalable production solutions and strong cross-functional collaboration.

Lead the development of robot policies, focusing on task planning, computer vision, and decision-making in robotics. Mentor teams, drive technical roadmaps, and collaborate on scalable AI solutions.

The Senior Robotics AI/ML Engineer at Analog Devices will develop AI-based robot policies, work on task planning and computer vision, and integrate AI into robotics systems, while collaborating with multidisciplinary teams.

Design, develop, and implement machine learning models and algorithms, collaborating with teams to enhance services and improve customer experiences through scalable ML solutions.

Nebius seeks a Senior ML Engineer for AI R&D focusing on applied research in reinforcement learning and agent training, requiring deep expertise in machine learning and software engineering.

Build and operate backend services and platform capabilities for storing, searching, and retrieving contextual insights. Manage and compress large context, create reusable APIs and tooling for teams, implement ML production workflows, and maintain evaluation and observability to ensure quality, performance, and reliability.

Lead the development of robot policies and task planning. Collaborate with cross-functional teams to create real-world robotics solutions, incorporating AI technologies and MLOps practices.

The Senior Machine Learning Engineer will deploy and maintain ML models in a SaaS environment, optimize models, and collaborate with engineers on AI features.

Manage and mentor a team of ML scientists, driving collaboration with engineering and product leads to deliver impactful ML products while enhancing team productivity.

Design and implement large-scale optimisation models using Gurobi; mentor junior engineers and collaborate with stakeholders; involve in decision systems using predictive signals.

Lead the development of high-fidelity simulations and validation workflows for robotic systems, focusing on sensor simulation and mechanical modeling to ensure reliable performance in real-world and virtual environments.

As a Senior Robotics Test Engineer, you'll validate sensor data, align simulations with real hardware, support ML data collection, and ensure safety in robotic operations.

The Sr Machine Learning Scientist will develop and implement ML models and algorithms, collaborate with teams, and drive insights to enhance services.

Design, develop, and implement machine learning models and algorithms, collaborate with teams to enhance AI/ML services, and ensure data quality.

Design and implement machine learning models, build scalable ML pipelines, and collaborate with cross-functional teams to enhance services using AI/ML solutions.

Lead development of high-fidelity robotics simulations and validation workflows: design custom sensor models, run FEA mechanical simulations, generate synthetic datasets, integrate simulation outputs into ML training, and oversee field validation to close the sim-to-real gap.

As an Applied ML Engineer, you will build and scale data pipelines for video generation, ensuring data quality and optimizing preprocessing workflows.

The Senior AI/ML Engineer at Nansen will develop AI models for blockchain data analysis, collaborating with teams to enhance platform capabilities and mentor junior engineers.