Top Python Jobs in Dublin

Lead Site Reliability Engineer ensuring reliability, scalability, and performance of Mastercard applications. Drive observability, automation, capacity planning, incident response, and compliance. Mentor engineers, enforce operations standards, conduct root-cause analysis and post-mortems, and collaborate early in development to build resilient, production-ready systems.

Lead Site Reliability Engineer ensures platform reliability, scalability, and performance. Responsibilities include production readiness, automation, observability, incident triage and root cause analysis, capacity planning, DevOps practices, cloud infrastructure management, risk and compliance, and mentoring junior engineers.

Support and validate IFP PCOR reporting applications by testing, data validation, and resolving issues. Build and maintain data validation and QA automation architecture, load and transform data, create user-friendly views, work with business stakeholders to gather requirements, and maintain data load processes and stored procedures.

Build and maintain Atlas DevOps tooling and SDKs (primarily in Go) to automate cloud infrastructure and integrations (CloudFormation, CDK, Terraform, Vault). Design and ship integration components, support customers via Level 2 rotation, and collaborate across teams to scale SDKs and automation.

The Quantitative Strategist role involves building predictive models, developing trading strategies, analyzing risks, and automating research tasks in a collaborative financial firm environment.

The role involves developing and managing distributed storage systems, ensuring reliability, and optimizing infrastructure performance. Responsibilities include defining SLOs and participating in an on-call rotation.

Support sales and delivery of legacy-to-MongoDB modernization engagements: run technical workshops, design scalable cloud/on‑prem solutions, build and demo containerized applications, advise account strategy, and travel to customer sites.

Design and deploy machine learning models (matchmaking, skill rating, recommender systems). Develop representation learning for player behavior, evaluate state-of-the-art methods, translate product problems into ML tasks, lead technical discussions, and collaborate with engineers to integrate models into production.

Lead complex data science projects to improve healthcare outcomes by building data solutions, collaborating with teams, and mentoring staff.

Design and build self-service platform tooling and "Golden Paths" to enable developer autonomy. Develop Terraform modules, CLI/APIs, GitHub Actions and GitOps pipelines (ArgoCD), integrate OPA for automated governance, and ensure observability (Prometheus/Grafana) across services.

Support cloud security by managing IAM across tools, maintaining security tooling and monitoring, investigating alerts, reviewing Terraform PRs for secure deployments, and tracking threat intelligence while learning cloud-native security practices.

The Staff Infrastructure Security Engineer will lead security initiatives, set architectural patterns, conduct security reviews, and mentor engineers while ensuring security in cloud infrastructures for GitLab.

As a Senior Data Scientist, you'll analyze complex healthcare datasets, apply advanced analytics, and collaborate to improve patient outcomes and operational efficiency.

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.

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.

The role involves researching and developing large language models (LLMs) with a focus on transformer architecture, data curation, distributed training, and optimization. Responsibilities include conducting experiments, collaborating with teams, and staying updated on deep learning advancements.

As a Site Reliability Engineer II at Klaviyo, you will ensure platform reliability and scalability, automate operational tasks, and improve systems through observability and collaboration with teams.

Build tooling, services, and reusable patterns to apply generative and agentic AI across products and developer workflows. Design and implement AI-enabled applications, evaluate models and frameworks, create integrations and automation for developer experience, and partner with stakeholders to prototype, validate, and scale AI solutions.

Build tooling, services, and reusable patterns to enable Agentic and Generative AI across products. Design and implement AI-enabled applications, evaluate models and frameworks, improve developer experience through automation, and partner with stakeholders to prototype and scale AI solutions.

Build tooling, services, and reusable patterns to apply Generative and Agentic AI to products and developer workflows. Design and implement AI-enabled applications, evaluate models and frameworks, create developer-facing integrations, and contribute prototypes through validation while improving developer experience and promoting best practices across the organization.

Build tooling, services, and reusable patterns to apply generative and agentic AI in products. Design AI-enabled applications and developer workflows, evaluate models and frameworks, develop integrations and automation, and partner across teams to prototype, validate, and scale production-grade AI solutions focused on usability and developer experience.

Build tooling, services, and reusable patterns for Agentic AI systems; design AI-enabled applications and developer workflows; evaluate models and frameworks; develop prototypes to production-ready solutions; improve developer experience through automation and platform capabilities; partner with stakeholders and evangelize best practices.

Build tooling, services, and reusable patterns to apply Generative and agentic AI to products and developer workflows. Design AI-enabled applications and integrations, evaluate models and frameworks, develop reusable services, improve developer experience via automation, and partner across product and engineering to prototype, validate, and scale AI solutions.

Design and build tooling, services, and reusable patterns to apply Generative and Agentic AI across products and developer workflows. Implement AI-enabled applications, evaluate models/frameworks, develop integrations, improve developer experience through automation, and partner with stakeholders to prototype, validate, and scale AI solutions.

Design and build tooling, services, and reusable patterns to apply Generative and Agentic AI to products and developer workflows. Implement AI-enabled applications, evaluate models and frameworks, develop integrations and automation, prototype products, and improve developer experience while collaborating with product, engineering, and business stakeholders.