Top Python Jobs in Dublin

Serve as the primary technical advisor for strategic GPU cloud customers: troubleshoot complex AI/ML issues, optimize GPU performance, guide deployments at scale, collaborate with sales and product teams, and translate customer needs into product feedback and solutions.

Design and implement cloud infrastructure and MLOps solutions for ML/AI customers. Advise clients, run PoCs and workshops, create IaC and technical documentation, optimize GPU training/inference pipelines, and act as primary technical liaison across product, support, and marketing teams.

Lead performance analysis and optimization of large-scale GPU/HPC clusters across hardware and software stacks. Troubleshoot real workloads, qualify and integrate new hardware, tune system configurations (networking, virtualization, kernel), support escalations, and collaborate with infrastructure teams and hardware vendors to ensure cluster performance meets expectations.

Join the Kubernetes product team to design and implement Kubernetes operators and addons, write high-quality Golang and Python code, debug issues, collaborate with a distributed team, mentor colleagues, and contribute to open-source integration and lifecycle management. Travel 2–4 weeks yearly for team events.

Serve as primary technical advisor for strategic GPU cloud customers, guiding design, deployment, and scaling of large-scale ML training and inference workloads. Troubleshoot complex AI/ML issues, optimize GPU performance, liaise with sales and product teams, and drive customer-aligned feature requests and solutions.

Lead applied research and system design for agent-native search: develop multi-stage retrieval, ranking, and grounding methods for LLMs working with real-time web data; define evaluation paradigms; optimize relevance, latency, and cost; deploy solutions to production and mentor the engineering team.

Advise AI-focused customers to design scalable AI solutions and manage large-scale GPU deployments. Deliver technical presentations, documentation, and webinars. Collaborate with engineering and product teams to prioritize and convey customer feedback.

Design, deploy, and optimize global enterprise wired/wireless networks and VPNs. Lead connectivity between branches, automate operations and monitoring, troubleshoot cross-region incidents, evaluate new technologies, and partner with telecom providers to manage SLAs and escalations.

The Data Engineer will design and maintain scalable data pipelines, optimize data infrastructure, monitor data quality, and enable analytics capabilities, ensuring alignment with business goals.

Lead and coordinate large-scale cloud platform programs across many teams, set goals and timelines, drive technical and procedural decisions, introduce reproducible processes, and align stakeholders up to C-level to scale regions and hardware generations.

Develop and maintain ABAP solutions in S/4HANA Cloud, own features and interfaces, integrate SAP with Make/Node/Python/Retool and the data warehouse, work directly with Finance stakeholders, investigate root causes, and learn modern SAP patterns (RAP, BTP, Released APIs).

Lead three engineering teams (Billing, Contracts, Livepatch) delivering and operating full-stack Golang services. Develop engineering managers, set roadmaps, uphold engineering practices, hire talent, collaborate with stakeholders, and ensure product and team health.

Lead three engineering teams owning business systems, data lake, and integrations. Oversee development, operations, hiring, manager development, engineering practices, roadmaps, and stakeholder collaboration to deliver business data and analytics solutions.

Lead user research by collecting and synthesizing qualitative and quantitative data, run A/B and usability studies, build lightweight prototypes and dashboards, promote research-driven decision making, scale research ops, and train teams to integrate user science across product and engineering.

Design, improve, and deploy large-scale ML models for real-time ad-tech applications; explore data sources, research solutions, run A/B tests, and collaborate with engineering to productionize models and monitoring.

Lead end-to-end ML work: define product problems as ML tasks, prototype and ship models (ranking, retrieval, LLM agents), build evaluation and monitoring, and measure marketplace impact (bookings, retention, GMV). Collaborate with engineering, product, and growth to deploy production models and improve LLM reliability.

Lead pre-sales technical discussions, demos, and POCs while owning post-sale success and growth for European enterprise accounts. Drive adoption, renewals, and expansions, collaborate cross-functionally, and translate technical capabilities into business value for security and engineering teams.

Customer-facing ML/GenAI engineer who advises customers, runs demos and strategic reviews, drives product adoption, partners with sales and engineering, and helps expand accounts by implementing best practices for production ML/LLM systems.

Design, build, and deploy large-scale distributed systems and high-throughput data pipelines. Lead architecture and technical initiatives, ensure performance, resilience, and SLAs, contribute production-quality code, and mentor engineers while collaborating with product and R&D leadership.

Design, build, and operate large-scale distributed systems and high-throughput data pipelines using Go and cloud-native technologies. Lead architecture, performance optimization, reliability SLAs, and code quality. Drive technical roadmap, mentor engineers, reduce technical debt, and collaborate with product and engineering teams.

Design, build, and deploy large-scale distributed systems and high-throughput data pipelines using Go and cloud-native technologies. Lead architecture decisions, ensure performance and resilience, contribute high-quality code, reduce technical debt, and mentor engineers while collaborating with product and engineering teams.

Design, build, and own large-scale distributed systems and high-throughput data pipelines. Lead architecture, improve performance and resilience, reduce technical debt, contribute code, and mentor engineers while collaborating with product and R&D.

The Staff/Principal Platform Engineer will lead the architecture and evolution of P2P.org's internal developer platform, overseeing Kubernetes, monitoring, security, and compliance, while mentoring engineers and collaborating cross-functionally.

Build and maintain the marketing automation backbone and AI agent integrations. Implement event tracking, data pipelines, CRM customizations, and cross-channel workflows. Prototype agent infrastructure, connect APIs/webhooks, automate go-to-market tasks, and produce analytics and attribution to support growth and experimentation.

Design and build scalable backend systems for PlanetScale's database platform (Vitess/Postgres), collaborate on distributed systems challenges, work autonomously and with customers, optimize performance, and mentor engineers while operating systems at production scale.