Python developer állások III. kerületben középiskolai végzettséggel

• Tackling complex technical challenges focused on scalability, reliability, and speed
• Maintaining a high-performance infrastructure that processes millions of events with low latency
• Collaborating with Data Scientists and Engineers to design and implement cutting-edge feature topologies

• Design and implementation of portfolio solutions for clients
• Ongoing management of portfolio solutions to meet client objectives and constraints
• Keeping up to date with client trends, industry news, events, research, and regulations

Performing tasks related to the position....

• Development of low-level software to integrate new Arm architecture improvements spanning Linux, Android, and related user-space components
• Development and optimisation with a focus on performance, energy conservation, and protection

• Magas szintű technikai és üzleti tanácsadás ügyfelek számára az Atlassian termékekkel és saját fejlesztésű megoldásokkal kapcsolatban
• Ügyfelek üzleti és IT folyamatainak felmérése
• Komplex megoldások tervezése, bevezetése és minőségbiztosítása

• Ownership of data engineering features, architecture, and code quality
• Design, implementation, and maintenance of Databricks-based data pipelines and workflows
• Building and optimization of ETL/ELT processes using Apache Spark on Databricks

• Kutatás és fejlesztési projektek végigkövetése a tervezéstől az átadásig
• Beágyazott vezérlők programozása C nyelven
• Prototípus berendezések beüzemelése
• Prototípus berendezések tesztelése
• Gépész mérnökökkel való együttműködés
• Villamos mérnökökkel való együttműködés

• 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

Performing tasks related to the position....

• Komplex AI megoldások fejlesztése ügyfelek számára
• RAG alapú megoldások fejlesztése Python/LangChain vagy Java/Spring AI technológiákkal
• Open source LLM-ek integrálása ügyfélrendszerekbe cloud és on-premise környezetben Kubernetes használatával

• Data ingestion processes from various sources into the Data Lake
• Design, development and optimization of complex data pipelines for reliable data flow
• Build, development and maintenance of frameworks facilitating construction of data pipelines

• Analysis of webshop and digital campaign performance across multiple brands and channels
• Building and maintaining campaign benchmarking databases using historical performance data
• Development of forecasting methodologies and performance estimates for future campaigns

• 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, and dataset documentation

• Training and fine-tuning models against curated datasets
• Running systematic hyperparameter and architecture experiments
• Building and maintaining evaluation suites including regression tests for model behavior and benchmark tracking

• Design, build, and launch AI and generative AI solutions
• Create scalable data pipelines and model deployment workflows
• Develop large-language-model and multi-agent products
• Set up automated testing, deployment, monitoring, and improvement

• Design and develop scalable cloud security automation solutions across multi-cloud environments
• Build and maintain platform services using modern engineering practices and a code-first approach
• Own and enhance CI/CD pipelines that enable secure, reliable and efficient delivery

Ownership of detection capabilities end to-end from problem framing and data through experimentation to production models and telemetry...

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

• Agent workflows with LangGraph / LangChain / PydanticAI / CrewAI
• Tool calling with APIs, databases, and internal services with clean contracts and safe error handling
• Hybrid systems with pre-built agents plus a thin custom orchestration layer

• 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