Python programozó diákmunka állások, munkák XVI. kerületben

• Development and operation of Keycloak/RHSSO-based IAM capabilities on Kubernetes
• Standardization of deployment, configuration, and troubleshooting practices
• Continuous improvement of reliability, security, and automation around the IAM platform

• Active partnership with sales and project managers to estimate, design, develop and deliver solutions
• Continuous communication with domain experts and product owners to understand core business needs and goals to synthesize requirement and quality standards

• Collaboration with data owners across departments to establish accurate and complete datasets
• Support for definition, documentation and maintenance of metrics and KPIs across all business domains
• Collection, cleaning, structuring and preparation of datasets for analysis and reporting

• Experience in different data science topics
• Independent delivery of data science projects with product-oriented mindset
• Engagement with clients to understand business objectives and translate into technical requirements
• Leading pre-sales technical discussions

• Support the management of user permissions across multiple tools and systems including AWS IAM
• Help maintain and improve security tooling including endpoint protection solutions and infrastructure monitoring tools
• Assist with monitoring security alerts and investigating unusual events

• Design of evaluation framework for scalable LLM-as-a-judge pipelines
• Development of rubrics and curation of high-quality golden datasets
• Optimization of judge prompts for automated scoring
• Full-stack product development contribution
• Integration of automated evaluations into CI/CD pipelines

• Design of complex and scalable data solutions on the AWS cloud platform
• Development and implementation of complex and scalable data solutions on the AWS cloud platform
• Design and optimization of data pipelines
• Writing clean, efficient and maintainable SQL and Python code

• Architect scalable inference services, APIs, and backend components for model-driven and LLM-powered product features
• Productionize AI and ML workflows with strong MLOps practices
• Define and implement evaluation frameworks for model quality, system reliability, latency, and cost

• Design, build, and ship production retrieval systems
• Own vector store selection and operation including scalability, latency, reliability, cost, and multi-tenant design
• Build and operate indexing and refresh pipelines including chunking, embedding generation, backfills, deletes, and versioned indices

• AI-alapú rendszerek és alkalmazások architektúrájának tervezése és fejlesztése
• Microservice és event-driven architektúrák tervezése és technikai irányvonal meghatározása
• Architekturális döntések meghozatala, beleértve a megfelelő technológiai és tervezési megoldások kiválasztását

Design and build knowledge tracing and longitudinal learner models that support mastery and progression features surfaced to customers...

• Providing technical assistance and guidance to data engineering and machine learning community
• Taking ownership of difficult technical problems
• Participating in the vision for data engineering through documents and conversations
• Getting buy-in from stakeholders and leadership

• Build and maintain scalable cloud infrastructures using modern services and best practices
• Proactive detection, analysis, and fixing of vulnerabilities and performance bottlenecks in cloud environments

• Accounting for intercompany transactions
• Accounting for special business events
• Monthly, quarterly, and annual financial close activities
• Reconciliation and investigation of billing and cost allocation queries
• Support of regional Treasury Center for inter-affiliate financing transactions

• Dashboard development with Power BI to visualize sustainability data and metrics
• Data integration from internal databases, external APIs, and third-party platforms
• Client reporting collaboration with sustainability team for customized visual analytics

• Build and operate multi-cluster containerized environments across cloud platforms
• Create end-to-end CI/CD pipelines for cloud-native applications and machine learning workloads
• Lead cost-optimization and FinOps initiatives for GPU, storage and data-egress spend

• Design and implement modern data architectures and lakehouse solutions
• Provide technical leadership throughout the project lifecycle
• Collaborate with business stakeholders
• Create effort estimations and provide technical expertise during the pre-sales phase
• Mentor 3-6 person project teams

• Design and ship production-grade agentic systems
• Take technical ownership of Compliance in a Box (CiaB) AI platform
• Architect and evolve AI reasoning layer and agent orchestration framework
• Build and maintain the GRC Brain (AI reasoning layer) and Agentic Cortex (agent orchestration framework)

Performing tasks related to the position....

• Mastering in integrating rendered layers and producing the final look of the shots
• Creating and managing additional lighting tasks