Senior AI/ML Engineer

Nasze wymagania: At least 5+ years of Data engineering experience with last 3 years experience in building Data processing At least 5+ years of experience in production-ready Python code development (e.g., microservices, APIs, etc.) At least 3+ years of experience in production-ready ML-related code development At least 1+ years of experience with GenAI (ChatGPT, Gemini, RAGs, prompt engineering) Practical experience in MLOps/LLMOps tools like AzureML/AzureAI Practical experience with Databricks 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 at least one of following domains: Data Warehouse, Data Lake, Data Integration, Data Governance, Machine Learning, Deep Learning, MLOps Practical experience in Spark/PySpark and Hive within Big Data Platforms like Databricks, EMR or similar 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 O projekcie: We are looking for an experienced AI/ML Engineer for one of our client. Zakres obowiązków: Working with Data Science teams to implement Machine Learning models into production Design, delivery GenAI solutions 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 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