Top Python Jobs in Dublin

Build and operate Grafana Labs' bare-metal platform: provision storage, networking, and Kubernetes clusters; manage control planes, CNIs, load balancing, scheduling and autoscaling; maintain Crossplane compositions and Terraform modules; collaborate with application teams; participate in on-call rotation and datacenter operations.

Design, prototype, and deploy ML models for personalization in mobile games. Implement and evaluate algorithms (including RL and generative methods), run A/B tests, convert prototypes to production via MLOps, monitor player data, and collaborate with product, engineering, and analytics teams to improve retention and monetization.

Operate and improve Alpaca's production infrastructure: on-call incident response, define SLIs/SLOs, enhance observability, ship infrastructure as code via GitOps, and strengthen PostgreSQL reliability (performance, migrations, HA/DR). Mentor teams on reliability and database fundamentals.

Build AI-native internal automations and agentic workflows to remove manual work across HR, Support, Ops, Finance, and Marketing. Design, ship, and maintain LLM-powered pipelines, scheduled tasks, no-code integrations, dashboards, and connectors; own intake-to-deploy lifecycle and document/hand off solutions to non-technical teams.

Support marketing analytics and forecasting by preparing performance reports, collecting/cleaning/analyzing data, developing dashboards in Power BI, assisting forecasting and planning cycles, contributing to cross-functional projects, and communicating insights through data storytelling.

Build and operate the internal AI platform used by 600+ developers: secure AI coding environments, AI-assisted CI and agentic AWS workflows. Own products end-to-end, improve developer experience, ensure reliability/observability/cost-awareness, participate in on-call, and capture reusable patterns and templates for broad adoption.

Speculative/talent-pool application for a range of IT roles (software engineering, cloud operations, QA, product/project, and business functions). Candidates should have IT or commercial education or equivalent self-taught skills, experience with at least one object-oriented language, agile mindset, strong English communication, teamwork, and willingness to learn and take responsibility. Successful applicants join a global talent pool for future matching roles.

Provide L2/L3 IT support, manage Azure services, corporate network devices, Active Directory, and cloud infrastructure, ensuring reliable IT Security systems while collaborating in a global team.

Develop and optimize algorithms for battery and renewable energy projects, analyze market data trends, and ensure algorithm performance.

Build end-to-end AI-native product features across frontend, backend, and model integrations. Design and deploy agent workflows, integrate LLMs, memory, and external tools, and ensure real-time streaming, low-latency interactions, reliability, observability, and robust fallback/recovery. Collaborate with ML, backend, and product teams and iterate based on real-world usage.

Build and ship end-to-end AI features, shaping model behavior and surrounding systems. Design prompts, tools, memory, and agent workflows; convert model outputs into reliable behavior; debug across model, infra, orchestration, and UX; optimize latency, cost, and reliability; and develop evaluation frameworks to measure real-world performance.

Own and ship core ML subsystems end-to-end for a proactive, long-horizon AI assistant. Work includes data preparation, training, evaluation, inference, debugging production failures, optimizing for latency/cost/reliability, and mentoring other ML engineers.

Nebius seeks a Senior ML Engineer for AI R&D focusing on applied research in reinforcement learning and agent training, requiring deep expertise in machine learning and software engineering.

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, build, and operate large-scale distributed metrics ingestion and alerting systems. Develop platform services, APIs, and tooling to enable observability, reliability, and agentic engineering across cloud-native production environments while collaborating with SRE and partner teams.

Lead 2nd-Line assurance over Monzo Europes risk framework: plan and execute effectiveness and thematic reviews across conduct, financial crime, fraud, credit, operational, ICT and information security risks; identify remediation, engage stakeholders, contribute to governance and risk culture, and report findings to senior management and the Board.

Lead QA for backend and distributed systems: design test strategies, automate API and backend tests, validate databases and message-driven workflows, test high-concurrency and fault-tolerant scenarios, integrate CI/CD, monitor production, debug incidents, and drive QA best practices and AI-assisted testing improvements.

Design, build, and harden Chromium-based browser components in C++ to power Menlo's AI/agent initiatives; apply networking and HTTP security expertise; integrate AI agents and MCP servers; build tooling in Python or Rust; deploy and operate cloud infrastructure (AWS/GCP, Kubernetes, Terraform); debug and optimize performance-critical systems; collaborate cross-functionally.

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, implement and support scalable AWS infrastructure; lead migration of containerised apps to AWS ECS; build Terraform IaC; improve CI/CD with GitHub Actions; configure Datadog observability; enforce security and reliability best practices; troubleshoot production issues and drive platform improvements.