ML/AI Engineer - Architect

ML/AI Engineer - Architect Poland Apply now Growth through diversity, equity, and inclusion. As an ethical business, we do what is right — including ensuring equal opportunities and fostering a safe, respectful workplace for each of us. We believe diversity fuels both personal and business growth. We're committed to building an inclusive community where all our people thrive regardless of their backgrounds, identities, or other personal characteristics.     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.   What We're Looking For:   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. UML notation. Good communication skills. Ability to work in a team and support others. Taking responsibility for tasks and deliverables. Great problem-solving skills and critical thinking. Fluency in written and spoken English.   What Will Set You Apart:   Experience in designing, programming ML algorithms, and data processing pipelines using Python. Good understanding of CI/CD and DevOps concepts, and experience in working with selected tools (preferably GitHub Actions, GitLab, or Azure DevOps). Experience in productizing ML solutions using technologies like Spark/Databricks or Docker/Kubernetes. BPMN, Archimate.