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Tasks: Building high-performing, scalable, enterprise-grade LLM/AI applications in cloud environment Working with Data Science teams to analyze requirements, build architecture conceptions, lead a implementation GenerativeAI and Machine Learning models into production (Tech Lead) Practical and innovative implementations of LLM/ML/AI automation, for scale and efficiency Design, delivery and management of industrialized processing pipelines Defining and implementing best practices in GenAI/ML models life cycle and ML operations/LLM operations Implementing AI /MLOps/LLMOps frameworks and supporting Data Science teams in best practices Gathering and applying knowledge on modern techniques, tools and frameworks in the area of ML Architecture and Operations Gathering technical requirements & estimating planned work Presenting solutions, concepts and results to internal and external clients Creating technical documentation including diagrams Requirements: At least 8 years of experience in production-ready Python code development (e.G., microservices, APIs, etc.) At least 8 years of experience in production-ready ML-related code development At least 2 years of experience in production-ready LLM-related code development, preferably based on the Retrieval Augmented Generation concept (RAG) At least 3 years of experience in Cloud Architecture Good understanding and experience with GenerativeAI models APIs (Large Language Models/Large Multimodal Models) Good understanding and experience with LLM orchestrators (e.G., Langchain, etc.) and concepts (RAG, in-context learning, fine-tuning) Good understanding of LLM evaluators, validators, and guardrails Good understanding of LLMOps concepts like GenAI operationalization- Scaling (e.G., LLMs serving, performance & API Gateways, LLMs tracking & monitoring) Experience in developing GenAI apps in rapid frameworks (e.G., Streamlit) Experience in MLOps/LLMOps tools like AzureML/AzureAI or GCP VertexAI Good understanding of ML/AI concepts: types of algorithms, machine learning frameworks, model efficiency metrics, model life-cycle, AI architectures Good understanding of Cloud concepts and architectures, as well as working knowledge with selected cloud services, preferably Azure or GCP We offer: Stable employment. On the market since 2008, 1300 talents currently on board in 7 global sites. “Office as an option” model. You can choose to work remotely or in the office. Great Place to Work® certified employer. Flexibility regarding working hours and your preferred form of contract. Comprehensive online onboarding program with a “Buddy” from day 1. Cooperation with top-tier engineers and experts. Unlimited access to the Udemy learning platform from day 1. Certificate training programs. Lingarians earn 500 technology certificates yearly. Upskilling support. Capability development programs, Competency Centers, knowledge sharing sessions, community webinars, 110 training opportunities yearly. Internal Gallup Certified Strengths Coach to support your growth. Grow as we grow as a company. 76% of our managers are internal promotions. A diverse, inclusive, and values-driven community. Autonomy to choose the way you work. We trust your ideas. Create our community together. Refer your friends to receive bonuses. Activities to support your well-being and health. Plenty of opportunities to donate to charities and support the environment. Modern office equipment. Purchased for you or available to borrow, depending on your location.