Data állások Budapesten (it programozás, fejlesztés)

• Vectorization of 2D data
• Manual 2D/3D GIS data manipulation
• QA/QC of point cloud classification
• Database handling
• Editing and preparing of 2D vector and 3D point cloud data for further processing

• Design and evolve end-to-end architecture across data ingestion, processing, storage, and delivery
• Define scalable data pipelines and batch or near real-time workflows
• Establish efficient data models, storage strategies, and access patterns

• Design, development, and optimization of core ML models, especially in Computer Vision and Deep Learning
• Development of efficient, scalable training and inference pipelines
• Mentoring junior ML engineers, reviewing code and sharing best practices

• Technical management of a team of 2-3 AI and cloud engineers focused on fast prototyping of AI/ML solutions in AWS cloud
• Mentoring and technical support to junior and medium teammates
• Acting as a trusted advisor to clients

• Development and customization of Microsoft Dynamics 365 applications using C#/.NET and Power Platform tools
• Building integrations between Dynamics 365 and Azure services such as Logic Apps and Functions

• Design and build the next generation of the single-security analytical modeling platform using C++23 and Python 3
• Influence the strategic development of analytical services in Aladdin by understanding business processes, identifying bottlenecks, and improving cloud-compute performance

• Development of infrastructure providing insights into operational cost and risk associated with Wise product ownership
• Enhancement of product to reduce Wise's cost for customers and enable smoother experience when additional information is required

• Learning existing system architecture, codebase, tools, and development practices
• Validating existing technical documentation and flagging any gaps or outdated content
• Highlighting blockers to knowledge transfer such as missing info, unclear logic, inaccessible systems

• Chunking and ingestion architecture with deterministic, validation-gated pipelines handling diverse enterprise document types with indexing and contextual enrichment
• Retrieval pipeline with vector search, BM25 hybrid retrieval, RRF re-ranking, embedding model selection and optimisation

Development and enhancement of the MSCI Index Development Platform and the IndexMetrics Real-Time application using modern software engineering practices, Python, Azure, and AI-assisted development tools...

• Design and implement core authentication and authorization including POST /auth/token endpoint, JWT validation middleware, and entitlement enforcement layer
• Build and maintain entitlement decision cache with invalidation on entitlement changes

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...

• Architect and lead the development of large-scale ML systems and model pipelines
• Introduce new ML systems such as traffic sign detection, building facade detection, and other computer vision-based solutions
• Define and drive the ML technical roadmap in alignment with company objectives

• Design the behavioural telemetry event and entity-state schemas and write the instrumentation specification
• Own the measurement standard including canonical definitions, naming, field ownership, versioned change control

• Design of behavioural telemetry including event and entity-state schemas and instrumentation specification
• Ownership of measurement standard including canonical definitions, naming, field ownership, and versioned change control

• Partner with engineering teams to identify the highest-leverage AI opportunities in the developer workflow
• Own foundational architecture and standards for how agents model releases and internal tools are evaluated and deployed internally

• Design and own end-to-end solution architecture across distributed systems and cloud environments
• Translate business requirements into scalable technical solutions with clear articulation of trade-offs

• Leading and growing multiple agile engineering teams
• Defining and owning the technical roadmap with stakeholders
• Championing responsible use of AI and automation
• Aligning technical strategy with business goals
• Mentoring and coaching engineers at all levels

• Working on the next generation vehicle's self-driving software
• Development of the internal data distribution and execution framework
• Integration of third-party frameworks
• Sensor data recording related tasks
• Development of human-machine interfaces and data visualization tools