Top Python Jobs in Dublin

The Quantum Information Researcher will advance quantum technology through research on error mitigation, collaborate with teams, and prepare research outputs.

Lead the development of quantum error correction protocols tailored for silicon spin qubits, collaborating with teams to enhance fault-tolerant systems and technical documentation.

The Principal Engineer will lead design verification for mixed-signal power converters, developing testbenches, verification plans, and metrics, while mentoring engineers and ensuring end-to-end verification readiness.

Lead customer migration implementations for Veeva Vault R&D applications. Provide expertise in data migration, mentor specialists, and support customer validation processes.

Develop and implement quantum-control software and tools, model realistic quantum circuits, write and integrate code for product features, mentor junior scientists, document and present results, and contribute to IP and research publications.

The Senior Backend Software Engineer will design, develop, and maintain scalable web applications, mentor junior engineers, and contribute to software development best practices in a quantum computing context.

The role involves architecting 3D object detection models, managing data pipelines, developing datasets for training, and mentoring junior engineers.

Work with senior traders to design, operate, and improve high-performance algorithmic trading strategies. Apply quantitative analysis to transform large data sets into trading models, solve real-market problems across desks (FX, fixed income, options, ETFs, energy), and collaborate with quants and engineers on strategy enhancements during a hands-on 10-week internship.

The Women's Winternship at Virtu offers an immersive experience in global trading for female students, focusing on trading tools, lectures, and teamwork, culminating in a final contest.

Lead design and delivery of data architecture and analytics platforms. Translate business needs into technical solutions, design data models, ETL/integration, MDM and data quality processes, optimise data warehouses, collaborate with data science/BI teams, produce HLD/LLD, manage technical delivery and stakeholder relationships within agile projects.

As a Senior kdb+ Engineer, you'll lead the development of high-performance kdb+ architectures for financial institutions, mentor junior developers, and ensure quality in code and delivery.

The kdb+ Engineer collaborates with users to define application requirements, develops and maintains code, supports project delivery, analyzes time-series data, and mentors junior developers.

Lead design and implementation of test strategies and automation frameworks (UI, API, end-to-end). Build and maintain reusable test utilities, integrate with CI/CD, analyze results, drive defect resolution, and promote shift-left quality practices across cross-functional teams.

Serve as a technical subject-matter expert for Agentforce/Data Cloud, advising strategic customers on architecture, performance, integrations, and AI-driven solutions. Run engagement playbooks, identify capability gaps, influence executives, drive optimisation and knowledge sharing, and mentor peers to ensure successful Data Cloud implementations and business value.

Lead end-to-end delivery of scalable AI/LLM-based solutions on the Salesforce platform: design and implement agentic intelligent agents, build data models and pipelines, integrate LLMs, resolve technical blockers, prototype rapidly, and advise customers as a trusted technical partner.

Build, operate, and improve reliable distributed platform services for internal development teams. Responsibilities include designing features, writing and reviewing maintainable code, troubleshooting production issues, improving scalability and observability, supporting internal users, and participating in on-call rotations. The role requires backend software development, cloud infrastructure, distributed systems, production support, and sound technical decision-making.

Build and mature DevOps automation processes and infrastructure. Own the GitLab foundation, including repository standards, CI/CD pipelines, testing, releases, and deployment coordination. Maintain automation and orchestration platforms, define cloud, virtualized, and physical infrastructure requirements, and establish safe AI-assisted automation policies. Partner with security, risk, systems, NOC, and business teams on requirements and deployment. The role requires Python, AWS, Ansible, Terraform, Docker, network automation, and release management expertise.

The AI Inference Engineer optimizes large language models for various environments, focusing on performance, scalability, and reliability in AI inference serving.

Lead detection and response across cloud, blockchain, and AI surfaces. Build detection coverage, run incident response, deploy SOC AI tooling, maintain SIEM/SOAR and orchestration, and collaborate cross-functionally to remediate threats and improve visibility. Participate in on-call rotation and support threat modeling, vulnerability scans, and custom tooling.

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.

Support and maintain mission-critical OT systems, including NMS, SCADA, and advanced DMS applications. Troubleshoot application, integration, and operational technology issues; develop interfaces and reporting functionality; manage data maintenance; support testing, upgrades, enhancements, and projects; coordinate with vendors and stakeholders; maintain technical documentation; and mentor junior team members.

Serve as a customer-facing technical partner in enterprise B2B SaaS sales. Lead discovery, qualify deals, validate technical feasibility, deliver tailored demonstrations, assess integrations and architectures, shape solutions with Account Executives, support trials, and ensure effective post-sale handoffs. The role also provides structured customer feedback to Product and requires cloud, operating system, scripting, GRC, cybersecurity, and audit knowledge.

Serve as a customer-facing Solutions Engineer supporting pre-sales for Vanta’s GRC platform. Partner with Account Executives to discover customer needs, qualify opportunities, validate technical feasibility, shape solutions, deliver tailored demonstrations, and support trials. Demonstrate automation of GRC programs across SOC 2, ISO 27001, and HIPAA frameworks, validate integrations and architectures, provide post-sale handoffs, and relay market feedback to Product. The role requires cloud, operating system, scripting, SaaS, communication, and project management expertise.

Designs and manages highly available AWS infrastructure, Azure DevOps CI/CD pipelines, Windows and Linux systems, and Docker/Kubernetes platforms. Implements infrastructure as code, automation, monitoring, logging, alerting, and reliability practices. Leads incident response, troubleshooting, root cause analysis, performance tuning, capacity planning, and deployment strategy improvements. The role supports security, compliance, platform modernization, and on-call operations while collaborating with development, platform, security, and application teams.

The Systems Engineer will manage server infrastructure, database systems, and network performance while collaborating with developers to ensure optimal operation and resource management.