Top Python Jobs in Dublin

Leads and coaches a cross-functional software engineering team building full-stack applications, APIs, data pipelines, and analytics products. Provides technical and product direction, designs complex features, partners on roadmaps and releases, drives innovation and quality, collaborates across teams, and contributes directly to implementation. The role requires scaling platform solutions, mentoring engineers, managing technical initiatives, and applying agile development practices.

Develop and deploy machine learning models for retrieval, reranking, indexing, search relevance, crawling, and content understanding. Build large-scale embedding and retrieval systems, evaluation pipelines, and quality metrics for agent-native search. Integrate models into high-throughput production services while balancing latency, quality, and cost. Collaborate on architecture and product decisions involving search, retrieval, and LLM-based systems.

Owns end-to-end test strategy, designs scalable backend and UI automation frameworks, integrates automated testing into CI/CD pipelines, performs exploratory testing, and advocates for testability and reliability across engineering and product. The role requires strong programming, Kubernetes and distributed-systems knowledge, debugging ability, and cross-functional ownership in a fast-moving startup.

Build, automate, secure, and operate cloud platforms supporting enterprise generative AI, LLM, RAG, and agent-based solutions. Develop Terraform infrastructure modules, CI/CD and GitOps pipelines, Kubernetes platforms, secure runtime patterns, AI integrations, observability, evaluation controls, and self-service capabilities. Partner with AI, application, data, security, privacy, risk, and architecture teams to move AI solutions from proof of concept to reliable, governed production services.

Build, deploy, and improve production machine learning systems for classification, retrieval, ranking, personalization, and evaluation. Develop efficient models and pipelines, optimize accuracy, latency, cost, and reliability, fine-tune existing models, monitor production performance, and use real-world feedback to drive improvements. Collaborate with engineering and product teams to deliver reliable AI-powered features.

Troubleshoot, restore, and maintain optical and IP networks in a 24x7 NOC environment. Own complex incidents from detection through resolution, perform multi-vendor diagnostics, execute maintenance and network changes, coordinate vendors and service providers, conduct root cause analysis, improve runbooks and monitoring, and mentor junior engineers. The role supports DWDM, CWDM, routing, switching, and transport technologies while coordinating incident communications and shift handoffs.

Leads advanced data analysis, develops dashboards, KPIs, and analytical models, and translates business problems into data-driven solutions. Works with complex datasets using Databricks, SQL, Python, BI tools, and cloud data platforms. Partners with engineering and governance teams, promotes analytics standards, mentors analysts, and communicates insights to stakeholders. Supports strategic decisions through descriptive, predictive, and prescriptive analytics.

The Senior Geochemist will serve as an embedded geochemical expert across international mineral exploration programs. Responsibilities include designing surface and drilling sampling programs, managing quality control, interpreting multi-element datasets, evaluating legacy data, supporting exploration targeting, training field teams, and collaborating with geologists, data scientists, and software engineers. The role requires extensive international travel, field deployment, technical judgment across multiple deposit types, and contributions to geochemical methods and technology development.

Deploy and operate Kubernetes clusters across cloud providers and edge locations. Build infrastructure networking, automation, secure runtime environments, observability, and workload isolation. Manage infrastructure as code with Terraform/OpenTofu and Ansible, improve reliability and capacity, and troubleshoot Linux, container, Kubernetes, networking, and cloud issues. Participate in on-call support and help secure platforms running untrusted customer workloads.

Manage and scale globally distributed blockchain infrastructure, design and operate production-grade services, implement infrastructure as code, maintain high availability, automate CI/CD workflows, monitor systems, and respond to incidents. The role requires Linux, networking, load balancing, configuration management, programming, observability, and troubleshooting expertise. Experience with Kubernetes, Nomad, and blockchain ecosystems is preferred.

Lead marketing analytics: own reporting frameworks, dashboards, and data quality; monitor KPIs; run A/B tests and experiments; build attribution, forecasting, segmentation, and budget-allocation models; automate workflows and drive continuous measurement improvements.

Develops data science and advanced analytics solutions for Sportsbook and Casino businesses. Responsibilities include building machine learning, personalization, promotion, player segmentation, and Lifetime Value models; conducting experimentation and causal analysis; partnering with commercial stakeholders; and delivering data-driven recommendations to improve marketing efficiency and business performance.

Develop and test mathematical models for sports betting pricing and risk management. Collect, clean, and analyze sports and betting data to identify trends and improve trading strategies. Use Python, C#, R, or C++ to automate quantitative analysis, collaborate with quants and traders, document methodologies, and support pricing and risk model improvements.

Designs, develops, deploys, and supports enterprise integrations and intelligent automations using MuleSoft, UiPath, APIs, RPA, workflow automation, and AI services. The role connects applications, data, and business processes across the enterprise, creates reusable integration frameworks, improves operational efficiency, supports digital transformation, and partners with architects, product teams, cybersecurity, infrastructure, and business stakeholders. Experience with enterprise platforms, cloud technologies, and Java, C#, or Python is required.

Design and scale backend services for AI-driven sales automation and agentic workflows. Own end-to-end features spanning databases, APIs, background processing, and integrations. Collaborate with product, AI, and frontend teams while championing code quality, testing, performance, security, scalability, and maintainable architecture. The role involves PHP and Python development, cloud infrastructure, asynchronous processing, third-party and LLM integrations, microservices, and multi-tenant SaaS systems.

Machine Learning Interns will own a scoped ML project, from problem definition and experimentation through implementation and results communication. They will analyze data, develop and evaluate models, contribute to applied AI research, write tested and maintainable code, and apply techniques such as NLP and graph-based modeling to ranking, search, discovery, and advertising problems. The role involves collaboration with engineering, product, and data teams in a hybrid Dublin office setting.

Develop and validate control software, algorithms, and protection logic for European air-cooled chillers. Responsibilities include MATLAB/Simulink model-based development, compressor and fan staging, safety and refrigerant mitigation controls, building-management communications, cybersecurity support, compliance, laboratory testing, troubleshooting, documentation, and technical collaboration across global engineering teams.

Design, develop, deploy, and operate reliable cloud-native platforms supporting large-scale ecommerce services. Improve reliability, scalability, observability, security, performance, automation, incident response, and CI/CD processes. Build and maintain Kubernetes-based infrastructure, analyze system performance, resolve incidents, conduct root cause analysis, and collaborate with internal customers and cross-functional teams.

Embed with strategic customers to design, build, and implement data-driven AI solutions that improve customer support automation and Fin adoption. Analyze workflows and business challenges, establish measurement best practices, prototype and scale AI tools, and collaborate with Sales, Success, Product, and Engineering. Feed deployment insights back into product strategy while translating complex technical analysis into measurable business outcomes.

Lead and mentor a data science team developing machine learning systems for threat detection and agentic AI. Set ML technical strategy, standards, roadmaps, and deployment practices; guide projects from research through production; collaborate with security, engineering, and product teams; develop advanced malware and behavioral threat models; communicate insights; and contribute to research, publications, patents, and hands-on technical work.

Build and maintain FinOps data pipelines, BigQuery and dbt models, cost attribution systems, forecasting and anomaly detection models, and cost-versus-revenue analytics. Identify and implement AWS and GCP savings opportunities, automate governance with Python, Terraform, and Lambda, and partner with Engineering, Finance, Product, and leadership on cloud costs, forecasting, reporting, and architecture decisions.

Support Web3 users and technical operations across Telegram, Discord, blockchain infrastructure, RPC services, and AI-powered support workflows. Triage node and synchronization issues, develop and troubleshoot Telegram Bots and Mini Apps, maintain knowledge-base content, coordinate urgent issue resolution, and document solutions. The role requires blockchain fundamentals, programming ability, technical troubleshooting, responsive communication, and five-day weekly availability.

Own and optimize connected go-to-market systems, including Salesforce, HubSpot, DealHub CPQ, marketing automation, and sales-engagement tools. Translate business requests into scalable solutions, automate manual processes, maintain data quality, build integrations, monitor reliability, and support EMEA users. The role requires hands-on Salesforce expertise, scripting, API knowledge, systems thinking, documentation, change management, and effective collaboration with business and engineering teams.

Own and optimize interconnected go-to-market systems including Salesforce, HubSpot, DealHub CPQ, and sales and marketing tools. Build automations, integrations, self-service solutions, and small tools; improve data quality; maintain reliable APIs and workflows; support EMEA users; document changes; and manage sandbox-to-production releases. The role requires strong Salesforce administration and development skills, systems thinking, scripting ability, and effective collaboration with business and engineering teams.

Own and improve connected go-to-market systems including Salesforce, HubSpot, DealHub CPQ, and sales engagement tools. Translate business requests into scalable solutions, automate manual processes, maintain data quality, manage integrations, monitor reliability, and support EMEA users. The role requires Salesforce development and administration skills, scripting, API knowledge, systems thinking, documentation, change management, and daily use of AI tools.