Junior python developer állások, munkák Budapesten

• Integrating rendered layers
• Producing the final look of the shots
• Creating and managing additional lighting tasks

• Creation of 3D rigs for different types of objects, animals and characters
• Collaboration with visual effects supervisor and Lead CG to determine best technical and creative approaches
• Delivery of work within established project targets and high quality standards

• Building and optimizing inference pipelines for large-scale model serving
• Working with frameworks like PyTorch, TensorRT, and vLLM to deploy models efficiently
• Implementing and optimizing ML models using techniques such as quantization, kernel fusion, and efficient batching

• Build and maintain simulation environments for mobile robotic perception and navigation
• Develop and integrate robotic behaviours and learning pipelines for reinforcement learning and motion planning in complex outdoor environments

• 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

• Design and implement cloud security controls across AWS, Azure, and/or GCP
• Deploy and tune Cloud Security Posture Management and Cloud-Native Application Protection Platform tooling
• Build security into Infrastructure-as-Code and CI/CD pipelines including IaC scanning and policy-as-code

• Biztonsági és kockázati értékelések végzése alkalmazások és rendszerek esetében
• Frontier AI szkennelési képesség beállítása és technikai eredmények elemzése
• Jira backlogok létrehozása, kezelése és megoldása biztonsági kérdések, kivételek és kockázati tételek esetén

• Implementation, configuration and maintenance of cloud-based infrastructure (IaaS/PaaS)
• Support of migration of on-prem applications to the cloud
• Troubleshooting and support of Linux and some Windows systems in virtualized cloud environments

• Nemzetközi csapat tagjaként hosszú távú tesztelési feladatok különböző projektekben
• Új automatizálási keretrendszer fejlesztése low-code tesztautomatizáláshoz
• A keretrendszer karbantartása, gondozása és folyamatos továbbfejlesztése
• Innováció és új technológiák aktív bevonása és alkalmazása

Agent workflows with LangGraph / LangChain / PydanticAI / CrewAI (routing, retries, fallbacks, timeouts, human-in-the-loop)....

• Support the integration of security best practices into the DevOps lifecycle
• Contribute to the implementation and continuous improvement of security services, CI/CD pipelines, and cloud infrastructure with a focus on automation and scalability

• Managing and migrating ETL pipelines between various source systems
• Validating pipeline build success and output data quality
• Communicating with business stakeholders and SME's regarding their respective data domain

• On-premise IT infrastruktúra üzemeltetése, támogatása és folyamatos fejlesztése
• Linux alapú rendszerek adminisztrációja
• Kubernetes klaszterek adminisztrációja
• Middleware komponensek adminisztrációja
• Automatizációs feladatok megvalósítása és karbantartása

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

• Operation and evolution of Kubernetes platform
• Building, configuring, and maintaining bare metal hosts and Kubernetes clusters to run GPU/AI workloads
• Design and operation of NVIDIA AI related software stack (Slurm, Run AI)
• Providing customized application support for AI related workloads

• Data pipeline development
• Data integration
• Data warehousing
• Data modelling
• Data quality and governance
• Performance optimization
• Collaboration with data scientists and analysts
• Technology selection
• Security and compliance
• Monitoring and troubleshooting

• Build and maintain scalable cloud infrastructures using modern services and best practices
• Proactive detection, analysis, and fixing of vulnerabilities and performance bottlenecks in cloud environments

• Design, build, and maintain robust CI/CD pipelines
• Manage and optimize cloud infrastructure on T Cloud Public, ensuring high availability and performance
• Administer and troubleshoot Linux and Windows systems in production environments

• 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