ML/AI Engineer

* The person we are looking for will become part of Data Science and AI Competency Center working in AI Engineering team. The key duties are: * Design, deliver and scale GenAI solutions * Practical and innovative implementations of LLM/ML/AI automation, for scale and efficiency * Working with Data Science teams to implement AI Agents and Machine Learning models into production * Design, delivery and management of industrialized processing pipelines * 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 * Defining and implementing best practices in ML models life cycle and ML operations/LLM operations * Gathering technical requirements & estimating planned work * Presenting solutions, concepts and results to internal and external clients * Creating technical documentation * At least 4+ years of Data engineering experience with last 1 year-experience in building Data processing * At least 4+ years of experience in production-ready Python code development (e.g., microservices, APIs, etc.) * At least 1+ years of experience with GenAI (various LLM models, agents, RAGs, prompt engineering, MCP, specification-driven-development) * At least 2+ years of experience in production-ready ML-related code development * Additionally for all levels: * 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 * Experience in designing and implementing data pipelines * 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. * Nice to have skills & knowledge: * Experience with LangGraph, FastAPI, CosmoDB, Redis, SpyGlass, Kubernetes * Experience in designing, programming ML algorithms, and data processing pipelines using Python * Experience in at least one of following domains: Data Warehouse, Data Lake, Data Integration, Data Governance, Machine Learning, Deep Learning, MLOps * Practical experience in MLOps/LLMOps tools like AzureML/AzureAI (or GCP equivalents) * Practical experience with Databricks * Practical experience in Spark/PySpark and Hive within Big Data Platforms like Databricks, EMR or similar * 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.