E learning állások, munkák it programozás, fejlesztés területen

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

• Owning net-new pipeline and revenue across the service lines
• Running and sharpening the outbound engine
• Managing and developing an SDR
• Refining sequences and account-based plays
• Keeping the tooling stack tuned with an external GTM partner
• Setting the bar for activity and conversion

• Owning a revenue target across data, advanced analytics, and predictive AI
• Leading executive-level client conversations, joining deals early to diagnose the business problem, structure a solution, and build the ROI case that gets the client to sign

• Contribution to Customer Platform team
• Delivery of high-quality NodeJS, TypeScript and React code with simplicity, performance, and scalability
• Design and implementation of client and database-related application features

• 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

• Owning the quality architecture for the Scoring engine
• Prioritizing test strategies based on real-world risk
• Standardizing reusable patterns for the repository
• Building reliable automated coverage across UI, API, and deep service layers
• Operating as a power user of AI-first IDEs

• 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

• 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

• 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

• 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

• Contribution to ID Verification team as an essential part of fraud prevention solution
• Delivery of high-quality NodeJS, TypeScript and React code with simplicity, performance, and scalability
• Design and implementation of cutting edge client and database-related application features

• Executing system data maintenance and administrative activities in Cornerstone and relevant learning management systems
• Providing non-systems related learning process support

• Building and maintaining dataset ingestion, cleaning, and versioning pipelines
• Designing and operating labeling workflows including quality control and inter-annotator agreement tracking
• Owning dataset testing including coverage analysis, class balance, leakage detection, and dataset documentation

• Leading and mentoring a team of ML engineers
• Owning model quality end-to-end from experimentation to production-ready artifact
• Conducting regular 1-on-1s for career development and feedback
• Removing blockers and ensuring team well-being

• Experience in different data science topics including machine learning, LLM, deep learning
• Independent delivery of data science projects with e2e product-oriented mindset
• Direct engagement with clients to understand business objectives and translate into technical requirements

• Conducting a comprehensive literature review of state-of-the-art end-to-end autonomous driving approaches and uncertainty estimation methods
• Evaluating and selecting suitable uncertainty estimation techniques for integration into end-to-end autonomous driving systems

• Development and optimization of AI applications for production and development processes
• Analysis of large production, quality, and process datasets
• Creation of dashboards and data models for data-driven decision-making
• Development of machine learning models for quality improvement

• Development of advanced AI solutions
• Collaboration across divisions to design, develop, and deploy machine learning models and AI applications
• Working with state-of-the-art AI technologies including generative AI, natural language processing, and computer vision

• Management and development of a team of 0 to 1 direct reports
• Support of business migration and transition into core company ERPs such as SAP S/4 Hana and E1 with emphasis on manufacturing module migration

• Development of cutting-edge CI/CD pipelines
• Streamlining systematic processes
• Maintenance of core gateways
• Ensuring security and integrity of software assets
• Trying out new technologies to improve and expand know-how
• Participation in cross-functional, international agile team