Python programme állások IX. kerületben (ai és automatizáció)

• Contribution to the development and implementation of the AI and digitalization roadmap for Procurement & Supply Chain
• Analysis of existing processes and identification of suitable AI use cases to improve efficiency, automate activities and strengthen knowledge management

• Design and implement automation for storage provisioning, capacity management, and operational workflows using Python, Bash, and IaC tooling
• Drive reduction of manual toil through scripted workflows and self-service enablement

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...

• Establish data feeds with custodian banks, data vendors, and other service providers
• Support senior leadership, clients, and the broader Data Team in executing analyses and providing data-driven answers to questions
• Fully automate and centralize existing data integration processes

• Execution and support of cross-product validation frameworks from the business and financial logic perspective
• Identification of quality gaps and recommendation of improvements aligned with firm-wide standards
• Ensuring AI-driven workflows meet defined quality thresholds

• Build-from-zero applications
• Bridge machine learning and product
• AI-accelerated development
• Real-time visualization
• End-to-end delivery of early-stage applications

• Writing reusable, testable, and efficient code mainly in Python
• Mastering the integration of user-facing elements developed by front-end developers with server side logic
• Integration of data storage solutions
• Handling security and data protection professionally and precisely

• Writing reusable, testable, and efficient code mainly in Python
• Delivering great user experience by the development of great user interfaces
• Handling security and data protection professionally and precisely
• Collaborative work to provide technical solutions and implement new software features

• Ownership of on-device inference
• Design and implementation of Android inference solutions
• Development and maintenance of native Android vision layer using C++ and Android NDK
• Creation of JNI bindings connecting native components to Kotlin application

• 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 of highly scalable services realizing AI/ML functionalities

• Writing reusable, testable, and efficient code mainly in Python
• Delivering great user experience by the development of great user interfaces
• Handling security and data protection professionally and precisely
• Collaborative work to provide technical solutions and implement new software features

• AI-Native Infrastructure: Modern, GPU-intenzív AI/ML keretrendszerek szoftveres alapjainak megtervezése és kiépítése.
• Deep Containerization: Komplex Docker image-ek faragása, kifejezetten GPU-kompatibilis, AI workload-specifikus erőforráskezelésre (NVIDIA-docker, CUDA optimalizáció).

• Design and build learner models including knowledge tracing and longitudinal approaches
• Shape the data foundation for learner modeling including defining relevant signals and building datasets
• Translate mastery and progression definitions into model targets and evaluation criteria

• 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 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

• Development of the test automation framework
• Development of test cases/steps
• Development of test tools
• Integration of testing tools into the automation framework

• Development and fine-tuning of AI models including LLMs, Agentic AI, and Generative AI systems
• Building and deploying robust AI applications and services on cloud platforms
• Design and implementation of efficient AI pipelines from data preparation to model deployment and monitoring

• Design and implement pipelines to ingest, clean, and transform data into Data Lakes and Data Warehouses
• Active monitoring and optimization of pipelines for performance and cost
• Configuration of pipeline deployments and management of environment settings using IaC tools and CI/CD

• Lead the design and implementation of scalable data pipelines and Lakehouse architectures
• Act as the design authority
• Solve the hardest technical challenges including optimizing high-load streaming pipelines, debugging complex Spark jobs, and designing generic frameworks

Work directly with clients, product owners, architects, and development teams to understand business and technical requirements and translate them into infrastructure and cloud architecture requirements...