Opis oferty
31920 - 35280 zł
Poland, Kraków
Senior AI/ML Python Engineer w Kraków, Polska is listed on Jobeax. Browse 110,000+ vacancies available.
Szukamy wysoce autonomicznego inżyniera AI/ML, który będzie w stanie samodzielnie projektować, budować, wdrażać, monitorować, zabezpieczać, zarządzać i optymalizować nowoczesne kompleksowe rozwiązania AI/ML i GenAI w całym stosie technologicznym (w tym uczenie maszynowe, LLM, RAG, agentowa AI, chatboty i operacje produkcyjne na skalę przedsiębiorstwa), w tym prognozowanie KRI, wykrywanie anomalii, NL2SQL i wiele innych. Twoje zadania Współpraca z interesariuszami biznesowymi i przekładanie wymagań biznesowych na bezpieczne, skalowalne i zgodne z przepisami rozwiązania AI, zachowując pełną kontrolę nad architekturą, rozwojem, automatycznym wdrażaniem i bieżącym wsparciem operacyjnym po produkcji. Projektowanie, budowanie i dostarczanie rozwiązań AI/ML klasy produkcyjnej od koncepcji do wdrożenia. Tworzenie asystentów AI, chatbotów, przepływów pracy opartych na agentach i aplikacji opartych na RAG. Projektowanie skalowalnych architektur danych, AI i chmury. Tworzenie interfejsów API, usług front-end i back-end oraz integracji korporacyjnych. Wdrażanie MLOps/LLMOps, monitoringu, ewaluacji i zabezpieczeń. Zapewnienie zgodności rozwiązań AI z wymogami bezpieczeństwa, zarządzania i zgodności. Wymagania Min. 7 lat doświadczenia w software engineering, w tym 3+ lata w dostarczaniu produkcyjnych rozwiązań AI/ML. Doświadczenie w realizacji i utrzymaniu end-to-end systemów AI, w tym chatbotów, asystentów AI lub rozwiązań agentowych. Ekspercka znajomość Python, architektury oprogramowania, testów automatycznych, API, mikrousług oraz środowisk chmurowych. Praktyczne doświadczenie z Docker, Kubernetes, CI/CD oraz platformami AWS, Azure lub GCP. Bardzo dobra znajomość nowoczesnych LLM (np. GPT, Claude, Gemini, Llama, Mistral) oraz budowy aplikacji opartych o GenAI. Doświadczenie w projektowaniu rozwiązań RAG oraz systemów agentowych z wykorzystaniem frameworków takich jak LangChain, LangGraph, Google ADK. Znajomość klasycznych technik ML oraz frameworków PyTorch, TensorFlow, Scikit-learn. Doświadczenie w obszarze MLOps, monitoringu, ewaluacji i optymalizacji modeli AI. Praktyczna wiedza z zakresu AI Security, AI Governance oraz tworzenia skalowalnych platform AI dla przedsiębiorstw.
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