Top Machine Learning Jobs in Dublin

Design AI behaviors, workflows, and user experiences, ensuring systems function reliably and integrate into user workflows. Collaborate with teams to define AI capabilities and evaluate system performance.

Manage the integration of global flight supply partners, optimize product specifications, monitor metrics like price competitiveness and API latency, and collaborate with engineering teams to improve partner onboarding.

The Staff Machine Learning Scientist will define ML features, mentor engineers, research algorithms, and develop prototypes, focusing on customer value.

This role involves leading the development of AI systems to replace lab toxicity experiments, focusing on end-to-end ML architecture, research on chemistry-biology correlations, and building innovative models. Candidates should have strong ML skills, engineering abilities in Pytorch and Python, and a passion for both science and technology.

The role involves analyzing biological mass spectrometry data, developing software tools, and scaling workflows for AI and human consumption in drug safety assessment.

The Engineering Manager will lead the AI Platform Team, overseeing infrastructure development, hands-on coding, and supporting ML teams while planning high-impact roadmaps and improving developer experience.

The Senior Machine Learning Scientist will identify ML opportunities, develop algorithms, analyze data, and collaborate to enhance customer experiences with AI solutions.

The Principal Product Manager will lead AI-driven pricing and intelligence systems for travel sectors, managing model lifecycles and cross-functional projects to ensure financial accuracy and performance insights.

The Senior Product Owner will lead the product roadmap for a data analytics solution, collaborating with various stakeholders to ensure strategic direction, market analysis, and customer engagement, while managing vendor relationships and delivery planning.

The Principal Engineer, Grid Insights Lead will oversee field deployment, software and data pipeline configuration, and collaboration with engineering teams to enhance energy solutions.

The Executive Director leads HEOR Consulting projects, manages teams, ensures client satisfaction, and drives AI integration within healthcare solutions while overseeing business development and strategic planning.

Design, build, and modernize cloud-native, event-driven microservices for payments. Embed and govern AI/ML-assisted workflows, improve developer experience with automation and IaC, drive reliability and observability, mentor engineers, and balance delivery with enterprise risk and compliance.

Drive end-to-end product development for iTero 3D imaging systems by translating clinical needs into software requirements, leading cross-functional agile teams, driving ML diagnostic initiatives from PoC to productization, analyzing clinical usage data for improvements, and embedding customer feedback into product decisions to enhance usability, performance, and clinical value.

Lead positioning, messaging, and go-to-market for FineReader and ABBYY's Document Parser/SDK. Drive developer ecosystem strategy, technical content, enablement, and GTM alignment while gathering market intelligence to inform product and growth priorities.

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.

Build core components of a diagnostic and personalization platform: backend data pipelines, frontends, services for genomic data ingestion, ML model integration, APIs, and cloud infrastructure. Collaborate with product and ML teams, iterate on prototypes and MVPs, and make architectural decisions supporting scalability and reliability.

Lead Vegetation Intelligence product, owning roadmap from ML detection models to customer-facing risk products. Advance detection models, integrate outputs into outage and ignition risk, run user research, and translate model capability into actionable B2B products used in the field.

Lead global finance systems strategy and roadmap (NetSuite, BlackLine, FloQast, Pontus), drive AI and automation in finance, govern integrations and SOX controls, partner with finance and engineering stakeholders, recruit and develop product and systems teams, and deliver outcomes like faster closes, reduced manual effort, and improved data integrity.

Dragonfly is seeking Software Engineers for various portfolio companies, focusing on crypto technologies. Engineers of all experience levels are needed across multiple stacks.

Design, build, and manage large-scale search and content recommendation systems using machine learning and personalization techniques. Collaborate with content, product, and business teams to define success metrics, drive AI product improvements, and maximize content value and user impact.

As an Engagement Manager, you'll ensure customer success in protein R&D by building relationships, tracking metrics, and leading cross-functional teams. You'll manage enterprise accounts and advocate for customers while aligning their needs with Cradle's offerings.

Lead development and productionization of TTS and voice-generation systems: train, fine-tune, evaluate models, deploy and optimize for inference, latency, scaling, monitoring, and reliability; translate research into production and define technical direction while collaborating with research, engineering, and product.

Lead legal counsel for an adtech company providing commercial, product, privacy, and regulatory counsel. Negotiate complex agreements, advise on global privacy and IAB standards, support product launches and AI use cases, manage data governance and incident response, oversee corporate compliance and outside counsel, and build scalable legal operations and contract workflows.

Lead the estimating product roadmap for an AI-powered construction SaaS: prioritize and ship MVPs, run rapid experiments, conduct user discovery with estimators, define success metrics, and iterate using data and user feedback.

Lead and grow multiple small, high-output engineering teams focused on AI-powered vulnerability management. Stay hands-on with architecture and code reviews, drive hiring and career development, ensure technical excellence, and coordinate cross-team priorities to deliver customer and revenue impact.