Top Python Jobs in Dublin

Lead Data Scientist developing high-performance AI solutions using machine learning, deep learning, NLP, and large language models. Responsibilities include researching emerging AI technologies, building prototypes and products, designing AI architectures and pipelines, contributing to patents and research papers, mentoring junior scientists, presenting technical direction, and collaborating globally on innovation and R&D initiatives.

Lead technical research and development of secure, scalable fund-services solutions using Sigma Computing and AWS. Design proofs of concept, data integrations, semantic layers, analytics systems, and supporting services. Oversee delivery from feasibility through deployment and monitoring, implement CI/CD and security controls, guide developers through code reviews, collaborate with business and technical stakeholders, and produce technical documentation, demonstrations, and leadership reports.

Leads distributed software engineering teams delivering strategic private equity technology solutions. The role remains hands-on across architecture, design, development, code review, troubleshooting, production support, and cloud-native implementation. Responsibilities include mentoring engineers, improving engineering practices, using AI-assisted development tools, managing delivery estimates and risks, partnering with stakeholders, and ensuring secure, reliable, high-quality software delivery.

Lead API platform transformation as a product, establishing governance, roadmaps, documentation, prioritization, and delivery milestones. Partner with business, engineering, operations, and product teams to manage risks, dependencies, stakeholder expectations, and testing. Use SQL and basic analytics to identify product opportunities and define success metrics such as adoption, latency, error rates, and satisfaction. Facilitate steering committees, guide technical initiatives, and promote collaboration across organizational silos.

Design, build, and scale AWS cloud infrastructure and AI-enabled systems. The role owns CI/CD pipelines, containerized and serverless applications, data pipelines, security, disaster recovery, high availability, automation, testing, and operational documentation. It collaborates with engineering, business, and operations teams to deliver reliable solutions aligned with organizational goals, while participating in Agile practices and evaluating emerging cloud and DevOps technologies.

Develops and scales enterprise AI solutions, including LLMs, conversational AI, generative AI, and agentic systems. Responsibilities include model development, deployment, monitoring, MLOps, API integration, testing, prompt engineering, architecture, and performance optimization. The role collaborates with business and technical stakeholders, delivers proofs of concept, translates business requirements into scalable solutions, and ensures compliance with security, regulatory, quality, and ethical AI standards.

Design, develop, and architect AI, machine learning, deep learning, and agentic AI solutions. Research emerging techniques, build scalable cloud-based systems, resolve technical and production issues, improve performance through testing, and contribute to CI/CD automation. The role also involves technical demonstrations, documentation, knowledge sharing, and collaboration with global teams to deliver innovative enterprise AI applications.

Leads investment fund performance oversight, governance, reporting, remediation, and regulatory implementation for EMEA funds. The role analyzes performance and pricing data, presents findings to boards and management, oversees fiduciary and investment-policy processes, supports product development, and drives automation and continuous improvement using tools such as Python, Power BI, and Excel. It requires extensive fund management experience, knowledge of EU and UK supervisory regimes, investment strategies, derivatives, pricing, and strong stakeholder and presentation skills.

Develop and scale product security automation platforms, including automated code analysis, security finding triage and verification, security signal analytics, and self-service finding management. Build tooling that integrates security earlier into the software development lifecycle. The role requires production software development with Python and TypeScript, cloud-native systems, microservices, Kubernetes, containers, CI/CD, and AI agents, with preferred experience in secure execution environments and database development.

Design and implement scalable Databricks data platforms, Lakehouse architectures, ETL/ELT pipelines, Generative AI solutions, RAG pipelines, multi-agent workflows, and MLOps capabilities. The role includes data quality governance, Azure integrations, feature-store and training-dataset development, CI/CD practices, mentoring engineers, and contributing to enterprise AI engineering standards.

Leads pre-sales technical architecture for Salesforce SMB customers across EMEA. Partners with sales teams, advises CIOs and CTOs, translates business needs into Salesforce solution architectures, conducts technical workshops and due diligence, and leads proof-of-concept demonstrations. The role requires hands-on technical expertise, cloud and integration knowledge, executive communication, customer relationship management, mentoring, and occasional travel.

Leads enterprise customer engagements to define AI strategies, architect Agentforce and Data Cloud solutions, oversee deployment programs, and drive adoption and measurable value. Coordinates delivery teams, manages stakeholders and risks, guides AI readiness and change management, and translates customer feedback into product improvements. Requires customer-facing enterprise SaaS delivery experience, technical advisory skills, programming knowledge, AI/LLM solution design expertise, and strong program management capabilities.

Build and operate developer productivity systems, including deployment services, CI/CD infrastructure, AI coding agents, internal tooling, and AWS serverless workflows. Improve build speed, test reliability, deployment safety, and developer experience across engineering teams. Own DevProd metrics, create self-service templates and CLIs, support progressive delivery, and lead cross-team migrations. The role combines backend software development, platform engineering, stakeholder management, and internal product ownership.

Lead development and deployment of AI-driven digital diagnostic technologies, build a diagnostics lab, optimize biomarker data insights, unlock internal and real-world data, and collaborate across data science, engineering, and clinical teams to deliver production-grade ML solutions impacting patient care.

Performs daily investment data operations, analyzes and resolves data quality issues, responds to helpdesk requests, researches investment data, and supports process improvements. The role includes root cause analysis, documentation, testing, user acceptance testing, vendor coordination, and participation in data management initiatives. It requires accurate, timely work with securities, mutual funds, managed accounts, indices, composites, and related reference data.

Design, train, evaluate, optimize, and deploy advanced machine learning models for drug discovery. Own the full model lifecycle, build scalable inference and MLOps pipelines, establish reproducibility and testing standards, validate models with scientific experts, and mentor teams. The role focuses on deep learning, graph-based architectures, foundation models, distributed training, model monitoring, and production performance across latency, throughput, cost, and reliability requirements.

Build and maintain tools, services, platforms, and Python libraries supporting data science and machine learning solutions. Collaborate with engineers, data scientists, and business teams; contribute to deployment pipelines, testing, monitoring, performance improvements, proof-of-concept projects, and reliable cloud-based systems using Python, AWS, Docker, and Kubernetes.

Build and deploy AI-powered tools that automate Workday implementation and configuration tasks. Integrate LLM and machine learning capabilities into production products, develop infrastructure and monitoring pipelines, and improve reliability, performance, and cost efficiency. Collaborate with product, engineering, implementation, partner, and enablement teams to translate deployment challenges into AI solutions. The role also involves contributing to agentic systems and growing AI engineering practices.

Supports 24x7 optical and IP network operations by troubleshooting complex incidents, restoring services, executing maintenance and changes, coordinating vendors and stakeholders, performing root cause analysis, and validating service stability. The role also develops runbooks, improves monitoring and operational processes, mentors junior engineers, supports network turn-ups, and coordinates with carriers, field technicians, and service providers.

Leads enterprise cloud and infrastructure security architecture across AWS environments. Defines security strategy, guardrails, IAM frameworks, threat models, detection capabilities, infrastructure-as-code and automation standards. Secures Kubernetes and EKS workloads, develops AI-enabled security frameworks, influences executive and board decisions, and delivers cross-functional initiatives. Also develops senior engineers, establishes technical culture, and sponsors emerging leaders.

Drive product and business impact through statistical modeling, experiment design, Bayesian marketing analysis, machine learning, NLP, LLM applications, and classifier implementation. Build growth metrics, monitoring pipelines, evaluation datasets, and AI trigger systems across search and Duck.ai. Analyze privacy-constrained data, deploy production-grade models, optimize SQL queries, and lead complex projects from scoping through production with minimal direction.

Own data modeling, analysis, reporting, dashboards, and analytical solution delivery for Finance and Operations. Build scalable datasets and reusable data models, automate reporting and reconciliation, improve KPIs, validate data quality, optimize queries, and translate business needs into actionable insights. Collaborate with technical and non-technical stakeholders while using modern cloud, development, and AI-assisted tools to improve analytical workflows and productivity.

Analyze large datasets using SQL to identify pricing, supply, market, competitor, and demand trends. Develop pricing and revenue optimization strategies for car rental and insurance products, build dashboards in Tableau or Power BI, and translate insights into practical commercial improvements. Collaborate with Revenue, Supply, Trading, Data Science, and Engineering teams to improve forecasting, pricing models, profitability, and business performance.

Designs, builds, tests, and ships full-stack software for Learnosity’s cloud-based assessment API toolkit. The role spans React and JavaScript front-end development, PHP and Python back-end services, database and search optimization, AWS infrastructure, and end-to-end feature ownership. Responsibilities include technical planning, architecture, debugging, testing, code review, mentoring, stakeholder collaboration, and introducing AI-assisted development and other technologies. The role is Dublin-based, requires regular office attendance, and includes an approximately one-week-on-call rotation every four to six weeks.

Analyze large-scale security telemetry, threat intelligence, endpoint, and detection data to identify trends, anomalies, and emerging threats. Build dashboards, reports, data pipelines, and KPI frameworks using SQL, Python, LogScale, or similar tools. Collaborate with data engineering, product, and engineering teams to ensure data quality and translate complex findings into actionable insights for technical and non-technical stakeholders.