Python programozó diákmunka állások XI. kerületben (it programozás, fejlesztés)

• 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

• 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

• 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

• 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)

• 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

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

• Lead the end-to-end implementation of data pipelines and GenAI applications on Databricks
• Design and maintain CI/CD, model serving, monitoring, and evaluation frameworks for AI production reliability
• Tune complex Spark jobs and LLM inference patterns for maximum efficiency and minimum latency

• Collaboration with cross-functional teams to create user-centered designs
• Design of intuitive and visually appealing interfaces for web and mobile applications
• Conducting user research, competitive analysis, and usability testing
• Creation of wireframes, prototypes, and high-fidelity mockups

• 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

• Leading end-to-end penetration testing engagements across web applications, APIs, cloud environments, Kubernetes, AWS, Azure, GCP, and internal infrastructure
• Simulating real-world attack scenarios to identify security risks before they become threats

• Development of highly scalable services realizing AI/ML functionalities
• Implementation of machine learning solutions addressing computer vision and NLP use cases
• Work with Large Language Models (LLMs) and perform prompt engineering tasks

• Monitoring configuration, maintenance and usage of environments with virtual machines and cloud based infrastructures (Kubernetes)
• Cooperation with platform engineers, software architects, delivery teams and operational units

• 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
• Developing highly scalable services realizing AI/ML functionalities

• Design and implement cloud security controls across AWS, Azure, and/or GCP
• Deploy and tune Cloud Security Posture Management and Cloud-Native Application Protection Platform tooling
• Build security into Infrastructure-as-Code and CI/CD pipelines

• Line management, coaching, and career development for a team of Full-Stack Engineers
• Performance management and professional growth fostering
• Fostering a culture of technical excellence