Python állások XVII. kerületben középiskolai végzettséggel

• Design process involvement 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

• Build and maintain dataset ingestion, cleaning, and versioning pipelines
• Design and operate labeling workflows including quality control and inter-annotator agreement tracking
• Own dataset testing including coverage analysis, class balance, leakage detection, dataset documentation

• Development and operation of data pipelines
• Building data layers in OneDataLake (ODL) Central Data Store Consumer (CDSC)
• Balancing business and IT demands to build modern and efficient pipelines in public cloud environments
• Integration of data preparations into managed processes

• Technical leadership post-sales for strategic customers in big data project design and implementation
• Identification and driving of new initiatives to turn data into actionable business value aligned with business goals

• Skálázható cloud-native adatarchitektúrák tervezése Databricks vagy MS Fabric platformokra
• Adatmodellek, sémák és tárolási minták kialakítása (lakehouse, Delta, Parquet)
• Batch és streaming adatok betöltési pipeline-jainak megtervezése
• ETL/ELT folyamatok és transzformációs stratégia meghatározása

• Coordination of operations together with Data Center, IaaS and PaaS layers
• Coordination and support of network lifecycle activities including installs, upgrades, changes, and firmware updates
• Management of network interconnections and related documentation

• End-to-end penetration testing engagements across web applications, APIs, cloud environments, kubernets, binary applications and internal/external infrastructure
• Simulation of real-world attacks to identify security risks before they become threats

• Training and fine-tuning models against curated datasets
• Running systematic hyperparameter and architecture experiments
• Building and maintaining evaluation suites
• Analyzing model failures and translating findings into dataset or training improvements

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...

• Design and maintain enterprise-wide data models including conceptual, logical, and physical layers
• Lead data architecture for core platforms and support cross-value-stream data requirements
• Define data standards, naming conventions, and modelling best practices

• Ownership of architecture and delivery of production-grade LLM systems and classical ML solutions
• Design, evaluation, and optimization of RAG pipelines including retrieval strategy, chunking, indexing, and monitoring

• Labeling of image data for training of object recognition
• Programming of data acquisition pipelines in Python or C++
• Frontend development of a browser client in Three.js
• Design of 3D props and environments in Blender and Omniverse
• Linux server administration, particularly DGX Spark and Jetson

• Design and implement cloud security controls across AWS, Azure, and GCP
• Build security automation using CI/CD pipelines, Infrastructure as Code, and Policy as Code
• Develop automated compliance checks and remediation workflows

• 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

• Csapatmunkában történő részvétel jó minőségű, hatékony üzleti alkalmazások létrehozásában
• A rendszertervezéssel kapcsolatos egyeztetési és dokumentációs feladatok ellátása
• Komponensek működési céljainak meghatározása, valamint a kimeneti követelmények és formátumok értékelése

• Building and operating Kubernetes platforms on Open Telekom Cloud
• Managing Infrastructure as Code with Terraform and Terragrunt
• Implementing GitOps delivery using ArgoCD
• Operating PostgreSQL and Apache Kafka on Kubernetes
• Integrating security controls into CI/CD pipelines

• Implementation and improvement of business objects for mobile network infrastructure in backend systems up to the API layer
• Development and maintenance of business objects including data models, backend logic, and APIs

• 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

• 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

• Technology architect with T Cloud Public hands-on experience
• Deep expertise in public cloud architecture
• Strong understanding of VPC networking
• Strong understanding of IAM & federation
• Strong understanding of cloud security architecture
• Strong understanding of Kubernetes & container platforms