Top Python Jobs in Dublin

The IoT Software Engineer will develop and harden Linux-based OS for IoT devices, manage Azure IoT applications, and ensure cybersecurity compliance.

The Data/BI Engineer will build and maintain data pipelines, create dashboards in Looker, and unlock insights from data to support business decisions.

Develop hardware architectures for SoC products, validate architectural choices, write specifications, and collaborate with engineering and customer-support teams.

Design, develop, and maintain scalable backend services for embedded systems, ensuring integration with hardware and providing technical leadership.

The role involves improving machine learning ranking models, implementing algorithms, and taking full ownership of machine learning systems within Quora's product.

As a Senior SDET, you will enhance testing practices, improve CI pipelines, mentor engineers, and ensure platform reliability through comprehensive testing strategies.

Lead on-chain and off-chain market surveillance: detect and investigate manipulation (wash trading, spoofing, front-running), build statistical detection models, conduct transaction tracing, produce real-time dashboards and reports, and collaborate with engineering to automate and integrate advanced surveillance tools.

Join a trading desk after intensive training to manage daily positions, execute strategies, monitor real-time risk, collaborate with developers/quants to refine models and automation, back-test ideas, and provide competitive pricing and execution in high-frequency crypto markets.

Build and maintain backend API services for a decentralized exchange, design and implement trade routing logic for cross-chain swaps, optimize performance and reliability, collaborate with cross-functional teams, and troubleshoot trade execution and API issues.

Lead architecture and build a greenfield, white-label consumer engagement and rewards platform. Own backend, infra, mobile/web products, tokenised reward integrations, APIs, monitoring, and hire and scale the engineering team while ensuring production readiness and compliance.

Lead developer relations and growth by producing technical docs, tutorials, and code samples; represent the project at global events; engage and support developers on Discord/Telegram/GitHub; identify friction in onboarding and work with product to improve SDKs and docs; build partnerships with Web3 and AI projects to drive adoption.

Lead design and implementation of Spark and Livy-based features for large-scale distributed data processing. Contribute to Apache projects, develop in Java/Scala/Python, debug production clusters, improve infrastructure, and collaborate across distributed teams to deliver enterprise-grade data engineering capabilities.

Perform technical security assessments, embed security into development pipelines, run vulnerability scanning and penetration tests, develop incident response plans and playbooks, lead incident response, monitor alerts, and train teams on security practices while collaborating with development and operations.

Design, build, and operate the infrastructure and platform services that power AI agent workflows in production. Ensure reliability, scalability, observability, and security of model-serving, orchestration, and compute layers. Build APIs, SDKs, IaC (Terraform), CI/CD pipelines, monitoring and incident-response processes, and collaborate with AI, data, and engineering teams to productionize agent prototypes.

Design, build, and maintain high-performance backend infrastructure and data pipelines for an AI-focused cloud security platform. Drive architecture and scalability improvements, collaborate with product and security research, deliver end-to-end features, and improve engineering practices with automation and robust testing.

Design and implement real-time telemetry pipelines and fault-tolerant integration layers between IT and OT systems for datacenter power and grid-aware workload control. Own architecture and delivery of safe, reliable control systems from edge to control plane.

As the AI Agents Solutions Architect at Kraken, you'll design and build an AI-native finance operating system, automating finance operations and ensuring compliance in a regulated environment.

The role involves leading technical teams to develop high-quality software, mentoring engineers, and contributing to open source projects. Responsibilities include planning, execution, and enhancing the Linux user experience across various teams and technologies.

Design and architect scalable backend services, develop robust governance systems, build SaaS solutions, and mentor junior engineers to enhance IoT platform capabilities.

Perform manual and automated testing across web, mobile, APIs, backend services, and blockchain integrations. Build and maintain Python-based test frameworks, investigate issues across distributed systems, analyze logs/metrics/network traffic, contribute to release validation and automation, and collaborate with product, engineering, and DevOps. Use AI tools to accelerate testing, support incident analysis, and proactively improve testing coverage and product reliability.

Lead design and optimisation of multi-channel email and CRM journeys, monitor Marketo health, run experimentation across nurture streams, develop lead nurturing/scoring frameworks, and build scalable marketing automation workflows and integrations.

Senior full-stack engineer responsible for end-to-end design, implementation, testing, deployment and support of backend (Python/Django) and frontend (Angular/TypeScript) applications in a regulated manufacturing environment, ensuring compliance, validation, and production readiness.

Lead development of scalable, high-performance backend-heavy full-stack services using Elixir, Python or Go and React/TypeScript/Next.js. Design and optimize systems, manage PostgreSQL and MongoDB, deploy on cloud (AWS/GCP/Azure) with Docker/Kubernetes, apply CI/CD, mentor engineers, and collaborate across teams.

Design, develop, and maintain Python and Go microservices for data ingestion and processing; integrate backend services with BigQuery and cloud data platforms; implement REST APIs; build scalable data processing pipelines using Apache Beam and Dataflow; test and troubleshoot distributed systems; review designs, estimate work, mentor junior developers, and drive performance and reliability improvements.

Design, develop, and deploy production-grade ML and AI solutions including LLM fine-tuning, RAG architectures, NLP pipelines, time-series forecasting, supplier risk and anomaly detection, scalable data pipelines, and RESTful integrations with enterprise systems.