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Munkakörhöz tartozó feladatok ellátása....

• Administrative support to the marketing team
• Managing invoices, contracts, and purchase orders
• Supporting marketing campaigns
• Managing inventory of product samples and POP materials
• Collecting materials and information for presentations
• Supporting preparation of monthly reports and analyses

• Build and operate deployment pipelines for AI services covering CI/CD, infrastructure-as-code, environment promotion, and rollback
• Deploy and operate model serving, batch scoring, and orchestration pipelines across development, staging, and production

• Ownership of data models and storage architecture behind AI systems across relational, graph, and retrieval-oriented data
• Building and operating APIs, backend services, and pipelines to keep data current and accessible

• Building and maintaining strong relationships with a portfolio of clients
• Acting as a key point of contact for client requests, questions, and day-to-day communication
• Supporting client meetings, preparing follow-ups, and ensuring agreed actions are tracked and delivered

• Leading a data engineering team comprising 5-6 consultants
• Overseeing project delivery
• Managing and mentoring the team
• Ensuring successful execution of data engineering projects
• Ensuring successful execution of ML/MLOps projects
• Ensuring successful execution of cloud migration projects

• Support aiSim project managers in day-to-day coordination of software development projects
• Work closely with software developers and cross-functional teams
• Record and track meeting minutes in Confluence
• Create and manage Jira tickets
• Communicate with internal and external stakeholders

• Participation in the whole lifecycle of development projects from planning to handover
• Maintaining existing cross-platform apps
• Developing cutting-edge projects while writing high-quality code
• Keeping up with the latest technology trends
• Communicating well with other team members

• End-to-end AI solution ownership
• Partnership with product managers and business stakeholders for problem translation
• Independent planning and execution of research and experimentation
• Design of AI solutions with system-level perspective

• Leading a data engineering team comprising 5-6 consultants
• Overseeing project delivery
• Managing and mentoring the team
• Ensuring successful execution of data engineering projects
• Ensuring successful execution of ML and MLOps projects
• Ensuring successful execution of cloud migration projects

• Dotnet alkalmazások fejlesztése és karbantartása C# és .NET Core technológia használatával
• RESTful API-k és mikro-szolgáltatások fejlesztése
• Adatbázisok kezelése és optimalizálása
• Szoftverek teljesítményének javítása és hibák keresése
• Meglévő kódok refaktorálása

• Build-from-zero applications powered by the HawkAI Engine
• Bridge machine learning models and real-time data pipelines into APIs and user interfaces
• Integrate AI-assisted development tools into software architecture and data integrity workflows

• Design, build, and operate the firm’s AI platform including shared services, APIs, SDKs, and tooling
• Drive architecture across scalability, reliability, security, developer experience, and cost

• Writing and maintaining clean, high-quality, and efficient code aligning with project specifications
• Executing comprehensive testing and seamless deployment of programs and systems
• Communicating technical information clearly and effectively with team members

• Management of big data, cloud engineering, and machine learning projects for EMEA customers
• Leading end-to-end customer projects from kick-off to project closing
• Managing project and team day-to-day operations
• Handling customer communications and resolving escalations

• Design, development, and deployment of scalable, resilient, and high-performance components for the Wise Assistant
• Ownership of intent detection systems, contact processing pipelines, and routing logic for automation solutions

• Managing day-to-day technical operation of bug bounty programs
• Reviewing vulnerability reports submitted by ethical hackers
• Reproducing and validating reported vulnerabilities
• Identifying valid findings, duplicates, invalid reports and known issues

• Design, build, and maintain large-scale distributed data systems
• Develop data processing pipelines using technologies such as Spark and streaming solutions
• Work on systems that evaluate and ensure the quality and integrity of large-scale knowledge graphs

• Development, customization, and maintenance of ServiceNow applications, modules, and integrations
• Collaboration with cross-functional teams to understand business requirements and translate them into technical solutions

• Design, build, review, test, and maintain Ruby on Rails features and services in line with Diligent’s agile engineering practices
• Own technical delivery for projects, epics, and major user stories, including solution design, implementation planning, and execution through to production