Programozó állások X. kerületben (it programozás, fejlesztés)

• 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, develop, and optimize scalable data pipelines for processing large-scale structured and unstructured data
• Ensure reliability, performance, and scalability of data systems
• Build solutions to handle real-time streaming data from multiple sources

• 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

• Development and improvement of football ball and player tracking algorithms using multi-camera systems
• Contribution to multi-view geometry solutions for accurate tracking across the field of play
• Support for approaches to handling occlusion and recovery in fast-paced sports scenarios

• 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...

• Design, development, and optimization of core ML models in Computer Vision and Deep Learning
• Development of efficient, scalable training and inference pipelines
• Mentoring junior ML engineers, code review and sharing best practices

• 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

• Design and build an automation test framework integrated into CI/CD pipelines and the SDLC
• Implement automated tests across API, integration, and end-to-end layers
• Write high-quality, maintainable test code with focus on reusability, stability, and execution speed

• Új technológiák bevezetése
• Termékfejlesztési igények implementálása
• Rendszertervezés
• Tesztelés
• Dokumentálás
• Kapcsolódó alkalmazás- és interfészfejlesztésekben való együttműködés a társszervezőkkel
• Minőségbiztosítási feladatok támogatása

• 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

• LLM/GenAI architektúrák és agentek tervezése
• Ügyfelek fejlesztési igényeinek felmérése, átlátása és rendszerezése
• Specifikációk és rendszertervek készítése
• Prototípusok és PoC-ok létrehozása
• AI-megoldások jó gyakorlat szerinti kialakításában való részvétel

• Understanding underlying data structure of an ERP system (Microsoft Dynamics 365 Finance & Operations)
• Creating technical specification documents for functional requirements
• Managing existing and creating new automations using Alteryx, Python, SSIS
• Creating reports and dashboards in Power BI

• Design, build, and maintain backend services and APIs using C#/.NET Core in a cloud (AWS) environment
• Contribute to the development of scalable and secure microservices supporting SaaS products
• Work with Angular to implement and support end-to-end features where needed

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

• Planning automated test cases
• Creating automated test cases
• Executing automated test cases
• Maintaining automated test cases
• Analyzing results of automated tests
• Documenting results of automated tests
• Reporting defects
• Collaborating with cross-functional team members

• 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)

• Architect and implement scalable AI/ML solutions on Azure or GCP
• Design and build AI solutions for sales use cases such as automated RFP/RFI ingestion, classification, and response generation
• Design and build intelligent document understanding solutions