Top Python Jobs in Dublin

Leads a remote engineering team building scalable Python and Golang microservices for Canonical’s software distribution marketplaces. Responsibilities include mentoring and developing engineers, managing delivery and expectations, shaping technical strategy and roadmaps, reviewing code, guiding architecture, maintaining engineering quality, and collaborating with product managers, architects, other teams, open-source contributors, and commercial partners.

Provides advanced technical support for Twilio APIs, SDKs, and software platforms through phone, email, chat, and other channels. Resolves complex customer issues, troubleshoots application and network problems, manages escalations and incidents, meets SLA targets, documents technical findings, identifies adoption and upsell opportunities, mentors teammates, contributes to knowledge articles, and participates in process improvement and on-call rotations.

Build and operate AWS-based data platforms for fleet telematics products, including streaming and batch pipelines, ETL, data quality validation, observability, retention enforcement, and customer reporting. Own data engineering workstreams from architecture and design through deployment and production monitoring. Optimize database performance, cloud costs, and large-scale data systems while investigating production data issues and ensuring compliance.

As a Quantitative Researcher, you will develop trading strategies, implement mathematical models, analyze data, and contribute to high-level research in a trading environment.

Conduct original research applying machine learning, deep learning, and NLP to extract patterns from large and unstructured datasets; implement and back-test algorithms in high-quality code; document findings and collaborate with trading teams to deploy research-driven models.

Lead investigations and incident response using SIEM and SOAR, design detection alerts, perform threat hunting across endpoints, network, application and logs, analyze compromises and malware, build playbooks and security tools, share findings to improve product/security posture, and mentor junior team members.

Design, build, and test software features for MongoDB products. Collaborate with cross-functional teams to deliver quality end-user features, balance delivery with R&D, and support users maintaining MongoDB deployments.

Design, deploy, and operate production ML models and MLOps workflows (real-time and batch). Partner with ML scientists and studios to integrate ML services into games, build CI/CD, model registry/feature store practices, monitor drift, prototype ML/GenAI solutions, and mentor engineering teams.

Build and productionize generative AI and classical ML solutions for healthcare: data preparation, feature engineering, model/prompt development, evaluation, deployment, MLOps, monitoring, retrieval/indexing, and responsible AI practices while collaborating with cross-functional stakeholders.

Design, characterize, test, qualify, and support production of MEMS timing devices and resonators. Perform simulations, laboratory evaluations, debugging, data analysis, and root-cause investigations. Develop test software and automation, collaborate with MEMS, ASIC, fabrication, assembly, quality, and product engineering teams, and communicate technical findings and project status throughout the product lifecycle.

Build and maintain Ergodic AI’s AI platform across back-end and front-end systems. The role involves developing with Python web frameworks and JavaScript/TypeScript, integrating with client technology stacks and workflows, applying AI, ML, and LLM concepts, and contributing to DevOps, cloud deployment, testing, and infrastructure practices. As an early-stage hire, the engineer will help shape the product and solve complex data and AI challenges.

Develop AI-augmented blockchain risk and threat intelligence systems, including autonomous monitoring and investigation workflows. Lead forensic investigations into crypto theft, fraud, and market manipulation. Research post-quantum cryptography and quantum threats to blockchain security, evaluate migration paths, and collaborate with internal teams, external stakeholders, and academic institutions to deploy emerging security tools.

Lead people analytics and BI initiatives supporting talent management, development, acquisition, and diversity programs. Develop talent metrics, dashboards, statistical analyses, predictive models, survey insights, and data-quality tools using Tableau, Power BI, R, Python, and SQL. Partner with stakeholders and executives to communicate actionable findings, improve reporting frameworks, standardize metrics, and provide training and support.

Design, develop, test, and maintain scalable backend applications, SDKs, and tools for AI Security solutions. Build RESTful APIs and multi-service systems, optimize performance and reliability, troubleshoot production issues, and collaborate with product, QA, frontend, and data science teams. Apply secure coding and modern architecture practices while contributing to cloud-native deployments, testing, and continuous delivery improvements.

Leads data and analytics consulting projects for infrastructure and real estate clients. Responsibilities include managing project teams, gathering requirements, developing data processes and models, designing data solutions, building dashboards, testing and assuring solutions, supporting decision-making, and preparing client communications and business-development materials. The role also involves client engagement, project delivery, business generation, and people development.

Build trusted relationships with mid-market and enterprise executives, understand business and technical objectives, and architect Stripe payment, SaaS, banking, and network solutions. Responsibilities include delivering demos, responding to RFPs, securing technical wins, advising on business value and execution strategy, collaborating with product, marketing, partners, and professional services, and supporting customer activations. Approximately 25% travel is required.

Lead and mentor a cross-functional engineering team building growth-critical platforms, AI-driven tools, automations, and user engagement systems. Partner with Product and Design to prioritize work, guide architecture, improve processes, and deliver reliable production features. The role combines people leadership with hands-on backend software development, technical decision-making, stakeholder communication, and team enablement across distributed time zones.

Lead AI transformation across Sales, Marketing, Customer Success, Partnerships, and Revenue Operations. Identify high-value opportunities, design and deploy production AI agents, agentic workflows, automations, integrations, and enterprise solutions, then drive adoption and measure business impact. Partner with functional leaders, make sound decisions about AI suitability, redesign operating models, improve reliability and governance, and mentor colleagues while establishing reusable standards across the organization.

Lead the architecture and evolution of scalable ETL and data-processing systems for customer product catalogs. Design reliable distributed systems, improve throughput and latency, strengthen fault tolerance and observability, and guide technical direction across teams. Mentor senior engineers, conduct architecture reviews, lead cross-functional initiatives, influence hiring and onboarding, and help shape the engineering organization’s long-term technical vision.

Leads client-facing data analytics and digital assurance engagements across infrastructure and real estate. Responsibilities include designing data-driven solutions, producing technical specifications, managing client accounts, assuring project delivery, developing teams, and driving business development, proposals, and new client relationships. The role requires expertise in analytics, business intelligence, cloud technologies, data engineering concepts, project controls, and digital solutions, along with strong communication, commercial, and people-management skills.

As a Quantitative Research Analyst, you will develop and test automated trading strategies using statistical techniques and algorithms, conduct research, and analyze data.

Design, build, and operate core platform services to improve availability, scalability, latency, and cost efficiency. Develop platform primitives (infra, databases, queuing), enable developer experience, and implement tooling for observability, self-healing, configuration-as-code, and cost optimization.

Build Paddle’s data science function and production decisioning systems from the ground up. Prioritize high-value use cases, personally deliver the first ML or agentic system, and own deployment, monitoring, experimentation, reliability, governance, and financial impact. The role will establish the production ML stack, collaborate across Product, Engineering, Risk, Finance, and Compliance, then hire and lead data scientists and ML engineers. Experience with regulated transactional domains, production ML operations, experimentation, and executive stakeholder management is required.

Build and operate Kraken’s internal AI platform, including governed integrations, authentication, internal tooling, evaluation systems, spend controls, identity and access controls, provisioning, vendor configuration, and policy enforcement. Provide technical enablement through documentation, deep dives, and office hours while supporting teams and administering the enterprise AI estate.

Own the systems powering customer acquisition across sales, marketing, and revenue operations. Build lead-generation, enrichment, ICP scoring, sequencing, deliverability, and personalization workflows. Integrate CRM, data, and automation tools using APIs and webhooks, maintain HubSpot data and workflows, operationalize buying signals, evaluate AI and GTM tools, and report on pipeline impact. Partner with sales teams to improve handoffs and automate manual processes.