E learning állások IV. kerületben (it programozás, fejlesztés)

• Serving as the dedicated client liaison during each project engagement
• Supporting clients through the process, receiving data disclosures, answering questions, and delivering the final product

• Design process of a SoC by integrating the latest Arm IP products
• Development of RTL code using System Verilog
• Running EDA tools to check the design and analyze results
• Using AI-assisted engineering tools to support development and debug
• Identifying and fixing bugs

• Contribution in SystemVerilog RTL verification and debug
• Formal bring-up of non-trivial IP blocks to achieve required quality levels
• Collaboration with engineers across design, performance modelling, validation, and implementation to meet functional requirements, performance, power and area goals

• Technical assistance and training to customers globally
• Mentoring partners on IP integration, configuration, and performance
• Investigating issues and finding solutions through RTL simulations
• Analyzing customer requests and issues and providing solutions

• Developing testbenches and test cases to verify the design to high standards
• Investigating alternative options for existing design or verification implementations
• Developing and trialling new processes and flows to be used by the verification teams

• Lead the evolution of design system with scalable components, patterns, and guidelines
• Partner with Product Managers, Engineers, Content Designers, and Brand Designers to deliver intuitive, user-centred experiences
• Influence product strategy through research, insights, and design thinking

• Leading engagements to build and productionize tailored AI applications in the Databricks platform
• Owning the technical delivery of AI solutions
• Leading technical scoping and designing high-level architectures for AI and Generative AI solutions
• Defining the roadmap for AI and Generative AI solutions

• Building, operating and improving production data pipelines using Python, Airflow, Kubernetes and related technologies
• Designing scalable data pipelines and data models for growing data volumes and processing needs

• Design and configure Master Batch Records within Rockwell PharmaSuite
• Translate manufacturing process requirements into compliant MES design solutions
• Ensure adherence to global templates, design principles, and regulatory requirements

You’ll make an impact by: • Writing and maintaining automated test-cases by using an internally developed test automation tool • Manual testing • Evaluation • Bug reporting...

• Design and build artificial intelligence and machine learning solutions for enterprise clients
• Operationalize AI and machine learning solutions combining custom models with cloud and third-party AI services
• Assess client needs and data for AI/ML solutions

• Technical leadership of manufacturing execution solutions on Siemens Opcenter Execution Process Enterprise (MES)
• Ownership of middleware architecture and integration layer using Opcenter Connect MOM
• Definition and governance of technical standards, coding guidelines, and architecture decision records

• Implementation, support, and optimization of SAP GTS solutions in international client environments
• Provision of expertise in SAP GTS Compliance Management and Customs Management processes
• Support of international rollout programs, cutover activities, and go-live phases

Understanding clients’ mid-term strategies and managing executive relationships with their business and IT leaders...

• Build and maintain SQL queries and reports that track bookings, pipeline coverage, and conversion
• Monitor CRM data quality to resolve issues at the source
• Analyze pipeline trends and support the weekly forecasting review cadence with clean, accurate data

• Technical consultation and client education
• Creation of feasible delivery plans for on-time, on-budget, and high-quality project implementations
• Design and implementation of high-performing, maintainable, and secure software aligned with industry best practices and company capabilities

• Implementation of transformation projects across sectors
• Management of workstreams largely independently with support from Delivery or Engagement Manager
• Leadership of junior consultants and clients in projects or workstreams
• Conducting client meetings and workshops to achieve project objectives

• Design and implement data fabric architecture across heterogeneous data sources and platforms
• Develop scalable ETL/ELT pipelines for batch and real-time data integration
• Integrate structured and unstructured data from databases, APIs, SaaS applications, data lakes, and enterprise systems

• 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