Top Python Jobs in Dublin

As a Backend Software Engineer, you'll design scalable backend systems, optimize database performance, and collaborate with front-end and DevOps teams.

The Product Analyst will analyze payment flows, identify growth opportunities, build dashboards, and collaborate with product managers for data-driven decisions.

As a Senior Impact Analyst, you will analyze sustainability challenges, design and manage interventions, and work closely with smallholder communities, emphasizing rigorous research and collaboration.

Partner with Account Executives to present Arize's GenAI observability platform, lead technical demos and discovery, design and run PoCs, advise on GenAI/LLM best practices, handle technical objections, and build relationships with technical and business stakeholders across prospective customers.

Design, implement, and operate scalable, secure AWS infrastructure for an AI VFX platform. Build and maintain CI/CD pipelines, containerized microservices (Docker/Kubernetes), IaC (Terraform/CloudFormation), monitoring, and automation. Collaborate with developers to improve reliability, scalability, and deployment processes.

Optimize large-model inference at scale: improve throughput, reduce latency and cost per token, build benchmarking harnesses, tune parallelism and quantization strategies, implement load-balancing in routing, and evaluate custom kernels and emerging inference hardware.

Design, deploy, automate, and maintain scalable cloud infrastructure and CI/CD pipelines. Lead cloud architecture, ensure security and compliance, mentor engineers, troubleshoot production issues, and improve operational efficiency using Docker, Kubernetes, Jenkins, Terraform/Ansible, and cloud provider services.

Design, build, and operate Threat Protection and ShadowAI services: scalable distributed systems and APIs that detect and control risky web and generative AI usage. Own features end-to-end, maintain availability and latency SLOs, write tests, perform code reviews, use AI-assisted tools, and collaborate with cross-functional teams to improve detection accuracy and production reliability.

Design, build, and scale high-performance data pipelines and infrastructure (ingestion, transformation, storage, modeling, serving) using ClickHouse, Postgres, Python and dbt. Manage data quality, reliability, and observability at terabyte and 500M+ address scale, collaborate with researchers and product, mentor engineers, and leverage AI tools to accelerate work.

Build and operate secure, scalable AWS backend services for digital health. Design, implement, test, and maintain serverless APIs and integrations; improve reliability, observability, CI/CD, and incident response; mentor engineers and contribute to architectural decisions across the product lifecycle.

Own and evolve the core data platform: warehouse design, dbt transformations, and production AWS pipelines. Refactor and harden API-driven data flows, ensure observability and testing, partner with backend and product teams, and contribute to data-aware backend features to deliver reliable, product-focused data.

Lead a hybrid QA team to own testing lifecycle from requirements to release. Design and run manual and automated web, mobile, and API tests, develop test frameworks, improve CI pipelines, mentor engineers, track defects, and ensure high-quality releases.

Design, build, and maintain the studio pipeline and artist-facing tools (launchers, publishers, loaders, review/notes). Create fast, responsive front-ends for web, Qt/PySide, and in-engine (Unreal). Integrate with Maya, Unreal, Nuke, and Perforce on Windows, extend the AYON pipeline, add AI-assisted features, own tools through their lifecycle, and collaborate directly with artists while managing your own work.

Serve as a subject-matter expert for Agentforce/Data Cloud, advising strategic customers on architecture, integrations, performance, and solution design. Identify capability gaps, run engagement playbooks, influence executives, build cross-functional relationships, and mentor peers while ensuring data governance, ethics, and measurable business ROI.

Build, enhance, and support proprietary middle-office treasury, collateral, and trade platforms. Develop backend and frontend features, design and deploy agentic AI workflows, contribute to CI/CD and testing, maintain documentation, provide third-level support, and investigate emerging technologies for continuous improvement.

Design, build, and maintain ELT pipelines and dbt SQL models for analytics; optimize performance, scalability, and costs; apply AI-enabled tools to improve engineering workflows; collaborate to translate requirements into production-grade data assets.

Lead design and build of a greenfield, cloud-native banking platform. Architect scalable, secure systems, write production Java code, mentor engineers, drive CI/CD, SRE, testing, API design, and collaborate with product, compliance, and business stakeholders to translate requirements into technical solutions.

Lead the implementation of security practices in cloud and hybrid infrastructure, focusing on AWS and Kubernetes security, continuous vulnerability management, and securely automating CI/CD pipelines.

As a Senior Data Scientist at Intercom, you'll analyze data to drive decisions, support product teams, build data pipelines, and influence product strategy using AI tools.

Develop and optimize large neural-network tabular models in Python. Profile training and inference pipelines, improve memory efficiency, latency, and throughput. Implement performance-critical components in Rust (and optionally C++), ensure numerical stability and reproducibility, collaborate with researchers to productionize capabilities, and maintain tests and documentation.

Build and maintain front-end and back-end systems for model interaction and large-scale inference. Develop APIs, session persistence, event-driven architectures, database integrations (Snowflake/Databricks), and monitoring/retry mechanisms. Collaborate with MLOps/DevOps to optimize deployment and ensure reliable, scalable model-serving workflows.

Build and maintain Extensions backend for enterprise LTM products: design distributed, reproducible, observable workflows; optimize latency and throughput; collaborate with data scientists; drive architectural decisions; write high-quality, tested Python code; and document best practices for production-scale deployments.

Research, develop, and productize data-science methods to improve NEXUS predictive performance on enterprise tabular datasets. Implement production-quality Python components, design experiments and benchmarks, handle real-world tabular data challenges, collaborate with Research and Engineering, and validate approaches on customer datasets to drive product features.

Design, build, and operate cloud infrastructure and Kubernetes clusters for GPU/ML workloads; implement GitOps, IaC (Terraform), CI/CD, monitoring, automation (Python/Bash), and cost-optimization alongside ML engineers.

Own and patch Chromium/Firefox C++ source to build an in-house stealth browser. Fix fingerprinting at the engine level (navigator, WebGL, canvas, fonts, Client Hints), eliminate CDP leaks, maintain per-OS fingerprint profiles, continuously rebase patches, build validation tooling, and debug detection issues to keep automation indistinguishable from real users.