Top Python Jobs in Dublin

Design, build, and operate enterprise reporting and analytics platforms. Create scalable ELT/ETL pipelines, master data foundations, and lakehouse/warehouse semantic models. Deliver Power BI datasets and dashboards, implement data quality, governance, DevOps practices, and cost-management data solutions. Partner with finance and stakeholders and provide technical leadership across architecture, deployment, and run-state support.

Build, operate, and automate Menlo Security's global cloud-native platform across GCP and AWS. Manage VM fleets and Kubernetes clusters, author Terraform IaC and Spacelift workflows, implement observability with Grafana/Prometheus/OTel, handle networking, DNS, certificates, and service mesh, and reduce operational toil through automation while participating in 24x7 on-call rotation and cross-team architecture and DR planning.

Lead product definition and delivery for AI research tools by engaging data scientists and researchers, translating workflows into detailed specifications, owning the roadmap, collaborating with UX and engineering, and aligning stakeholders to prioritize and deliver MLOps-focused features.

Build and maintain the marketing automation backbone and AI agent integrations. Implement event tracking, data pipelines, CRM customizations, and cross-channel workflows. Prototype agent infrastructure, connect APIs/webhooks, automate go-to-market tasks, and produce analytics and attribution to support growth and experimentation.

The Senior Software Engineer will design and develop high-quality web and mobile applications, ensuring code quality while collaborating with product teams and mentoring junior engineers.

Lead architecture and reliability for cloud infrastructure and Kubernetes, improve observability and IaC, drive resilience and incident response, mentor engineers, and shape the platform roadmap.

The role involves architecting AI solutions for compliance, ensuring regulatory adherence, automating processes, and enhancing team capabilities through technology and training.

Own and scale half-hourly forecasting models for frontline workforce demand, lead end-to-end client launches (data validation, model selection, UAT, monitoring), join client calls, build stakeholder relationships, and maintain production ML systems that handle messy data and feedback loops.

Lead user research by collecting and synthesizing qualitative and quantitative data, run A/B and usability studies, build lightweight prototypes and dashboards, promote research-driven decision making, scale research ops, and train teams to integrate user science across product and engineering.

Lead three engineering teams owning business systems, data lake, and integrations. Oversee development, operations, hiring, manager development, engineering practices, roadmaps, and stakeholder collaboration to deliver business data and analytics solutions.

We are seeking a software engineer to build and validate resilient distributed systems, enhance CI pipelines, and improve testing strategies for cloud applications.

Join Canonical's Talent Science team to assist in hiring processes using data analysis and behavioral science. Ideal for recent graduates with a psychology background, the role offers opportunities for analytical project work and stakeholder relationships.

Join the Kubernetes product team to design and implement Kubernetes operators and addons, write high-quality Golang and Python code, debug issues, collaborate with a distributed team, mentor colleagues, and contribute to open-source integration and lifecycle management. Travel 2–4 weeks yearly for team events.

Lead the Talent Science team ensuring data-driven processes for recruitment, coaching team members, and delivering strategic project outcomes.

Lead three engineering teams (Billing, Contracts, Livepatch) delivering and operating full-stack Golang services. Develop engineering managers, set roadmaps, uphold engineering practices, hire talent, collaborate with stakeholders, and ensure product and team health.

Define and scale the AI platform infrastructure at Connectly to optimize conversational AI agents. Collaborate with technical teams for platform services, integration, and analytics.

Design, maintain, and optimize HLR/HSS/UDM subscriber templates and roaming logic. Lead Full MVNO profile deployments, collaborate with roaming partners and system integrators, define HLR/HSS KPIs, and troubleshoot signalling using Wireshark and roaming platforms.

Build, implement, and deploy agentic, LLM-powered platforms and RAG pipelines for enterprise clients; integrate with APIs, data platforms, cloud/on‑prem systems; configure Kubernetes, orchestrate multi-agent workflows, and lead technical consulting engagements with frequent European client site travel.

Design, implement, and maintain a low-latency real-time risk engine for perpetuals, spots, and prediction markets. Build VaR/ES and Greeks aggregation, margin and liquidation models, position limits, tail-risk models, dashboards/alerts, backtests, and circuit breakers to protect against extreme market conditions. Collaborate with trading infrastructure to meet <50ms P99 latency.

The AI Applied Scientist Intern will tackle complex problems using deep learning, statistical analysis, and large datasets, collaborating with a team to implement AI solutions that generate economic impact.

Develop and productionize avatar-centric video diffusion models: incorporate multimodal conditioning, enable real-time long video streaming, improve lip-sync and motion realism, build evaluation frameworks, collaborate with data teams, and translate research into product features.

Responsible for ensuring reliability, availability, and performance of cloud production systems, leading incident response, automating workflows, and improving system observability and scalability.

The Backend Software Engineer will develop and maintain backend systems for data processing related to coffee farming, utilizing Python and PostgreSQL. Responsibilities include feature development, problem-solving, and adapting systems to regulatory changes while ensuring system resilience.

Design, improve, and deploy large-scale ML models for real-time ad-tech applications; explore data sources, research solutions, run A/B tests, and collaborate with engineering to productionize models and monitoring.

The AI Platform Engineer will design AI frameworks and tools, enable AI feature integration, create reusable components, and ensure best practices for AI usage across teams.