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What you would be doing in this position: •Manage day to day tasks related to warranty extension processes •Maintain and regularly update the SVABA tracking file •Assist in administering and updating product related content on the Digram platform •Provide support with additional operational and...

• Design, develop, deploy, monitor, scale, and troubleshoot ML and LLM-based systems that power shared AI services across the platform
• Build secure, high performance microservices and platform components on AWS, owning services end-to-end from implementation through deployment and production monitoring

• 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

• Design new features in a flagship SaaS product
• Code new features in a flagship SaaS product
• Review new features in a flagship SaaS product
• Test new features in a flagship SaaS product
• Refactor legacy software components
• Participate in large-scale design of the future state of the product

• 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

• Design, develop, and maintain scalable fullstack applications using .NET and Angular
• Integrate and manage messaging systems such as Kafka and RabbitMQ
• Deploy and manage applications using Docker and Kubernetes in AWS environments
• Work with various databases including PostgreSQL, MSSQL, and Couchbase

• 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

• 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

• Nemzetközi értékesítési folyamatok koordinációja
• Értékesítési pipeline, forecast-adatok, ajánlati és rendelési státuszok kezelése
• CRM-rendszer használata és adatellenőrzés
• Értékesítési riportok, kimutatások, státuszjelentések és vezetői összefoglalók készítése

• 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

• Writing production-quality, well-tested scraper code in Python
• Learning the architecture of the collection platform including scrapers, proxy layer, queues and enrichment API
• Debugging issues across multiple components using logging, monitoring and alerting tools

• Creation and preparation of 3D assets, environments, and scene layouts for Omniverse and OpenUSD workflows
• Assembly of digital-twin scenes for industrial, facility, product, or enterprise visualization use cases

• 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

Design, develop, test, document, and deploy high quality Salesforce solutions leveraging the latest capabilities of the Einstein 1 Platform, Lightning Web Components, and modern Apex patterns...

Design, develop, test, document, and deploy high quality Salesforce solutions leveraging the latest capabilities of the Einstein 1 Platform, Lightning Web Components, and modern Apex patterns...

• 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