Python állások XI. kerületben (it programozás, fejlesztés)

• 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

• Support transmission system operators and distribution system operators in planning the power grid of the future
• Work directly with clients as part of international consulting project teams
• Perform power system analyses including power flow, voltage, short-circuit, N-1, redispatch

• 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

• Design, implement, and optimize compiler passes and transformations using LLVM/Clang or GCC
• Build and maintain robust toolchains
• Support new and complex architectures in compiler backends
• Work on architecture-agnostic and IR-level optimizations
• Work on silicon specific optimizations

• 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

• 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

• 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....

• Kollaboratív robot (Universal Robots) vezérlőalgoritmusok fejlesztése és karbantartása Python nyelven
• Algoritmusok tesztelése, élesztése és beállítása a helyszínen
• Admittance/impedance alapú erőszabályozás implementálása és finomhangolása

• 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

• 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

• 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

• Technical onboarding of TelCo and OSS applications onto Kubernetes-based platforms
• Contribution to Site Reliability Engineering through automation of operational tasks and creation of enhancements

• 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

• Integration of security best practices into the DevOps lifecycle
• Implementation and continuous improvement of security services, CI/CD pipelines, and cloud infrastructure with focus on automation and scalability

• Leadership in integration of security best practices into DevOps lifecycle
• Architecting, implementing, and continuously improving security services, CI/CD pipelines, and cloud infrastructure
• Design and enforcement of secure configuration management, secrets handling, RBAC, and network policies

• 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

• 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