Python programme állások Budapesten (it programozás, fejlesztés)

• collaborating on the design and development of ML‑based applications and their backend components
• helping to select the most applicable solutions for a given business problem
• writing clean, efficient and well‑documented code
• contributing to our MLOps processes

Technical and business support for GSCF applications supporting daily operations, fund accounting, financial reporting, and data processing functions...

• Co-design and implement QA workflows using statistical diagnostics, validation rules, and anomaly detection techniques
• Apply AI/machine learning tools to identify inconsistencies, missing values, or suspicious patterns in large-scale asset datasets

• Contribute to MDM strategy development
• Contribute to IT projects, developments to ensure the satisfaction of stakeholders
• Lead the professional execution of solution design, implementation and unit testing activities
• Participate in ERP related projects as Developer

• A vállalat teljes szoftverarchitektúrájának és fejlesztési szabványainak szakmai támogatása és folyamatos fejlesztése.
• Mikroszolgáltatás-alapú, skálázható platform továbbfejlesztésének irányítása.

• AI-platformok üzemeltetése fejlesztői, teszt- és éles környezetben
• AI modellek teljes életciklusának támogatása (deployment, monitoring, lifecycle management)
• Azure-alapú cloud security megoldások kialakítása és működtetése
• AI rendszerek biztonsági felülvizsgálata és kockázatelemzése

• Vállalati DevOps platform fejlesztése, üzemeltetése és optimalizálása.
• Azure-alapú production, test és development környezetek támogatása.
• Infrastructure as Code megoldások implementálása és karbantartása Terraform használatával.

• Design, develop and maintain software, tools and applications across the Baseball tracking platform
• Modernise and improve existing software systems
• Develop cross-platform C++ applications and visualisation components
• Participate in code reviews, pair programming and agile ceremonies

• Design and develop automation frameworks across frontend, backend, desktop, API, and data-driven systems
• Establish testing patterns and best practices for long-term maintainability
• Develop and maintain automated UI and end-to-end test suites using Playwright or Cypress

• Development and fine-tuning of AI models including LLMs, Agentic AI, and Generative AI systems
• Building and deploying robust AI applications and services on cloud platforms
• Design and implementation of efficient AI pipelines from data preparation through model deployment and monitoring

• Writing reusable, testable, and efficient code mainly in Python
• Mastering the integration of user-facing elements developed by front-end developers with server side logic
• Integration of data storage solutions
• Handling security and data protection professionally and precisely

• Writing reusable, testable, and efficient code mainly in Python
• Delivering great user experience by the development of great user interfaces
• Handling security and data protection professionally and precisely
• Collaborative work to provide technical solutions and implement new software features

• Writing reusable, testable, and efficient code mainly in Python
• Mastering the integration of user-facing elements developed by front-end developers with server side logic
• Integration of data storage solutions
• Handling security and data protection professionally and precisely

• Design of evaluation framework for scalable LLM-as-a-judge pipelines
• Development of rubrics and datasets including comprehensive grading rubrics and high-quality golden datasets
• Optimization of judge prompts for automated scoring alignment

• Writing reusable, testable, and efficient code mainly in Python
• Delivering great user experience by the development of great user interfaces
• Handling security and data protection professionally and precisely
• Providing technical solutions and implementing new software features collaboratively

• Design, build, and ship production retrieval systems
• Own vector store selection and operation
• Build and operate indexing and refresh pipelines
• Implement semantic and hybrid retrieval
• Own retrieval evaluation as a first-class system
• Make and defend the core tradeoffs of the domain

Architect, build, and operate scalable inference services, APIs, and backend components for model-driven and LLM-powered product features...

• Design and build knowledge tracing and longitudinal learner models that support mastery and progression features surfaced to customers
• Define what "mastery" and "progression" mean operationally: constructs, model targets, and evaluation criteria aligned to learning outcomes and product requirements

• Building transformative AI capabilities from the ground up
• Developing user-facing features with conversational and agentic AI technologies
• Experimenting with generative AI models and techniques
• Tackling challenges at the intersection of AI and enterprise software

• Leading a team of 2-3 AI and cloud engineers focused on fast prototyping of AI/ML solutions in AWS cloud
• Providing mentoring and technical support to junior and medium teammates
• Acting as a trusted advisor to clients