Information about the project:Industry: bankingRate: up to 165 pln/h net + VAT, B2BLocation: Warsaw/Łódź/Gdańsk/Gdynia - hybridSummaryThe primary objective of this role is to manage the complete lifecycle of machine learning models, ensuring their optimal performance, reliability, and integration in business processes through effective use of MLOps practices.Main Responsibilities Managed the lifecycle of machine learning models from development to deployment and monitoring, ensuring optimal performance and reliability. Implemented MLOps principles, including continuous integration, continuous delivery, testing, and monitoring, to streamline machine learning operations. Worked collaboratively with use case teams to design and deploy Machine Learning models. Key Requirements Proficiency in programming languages like Python and Spark (minimum 5 years). Understanding of algorithms and data structures, with knowledge of statistics and linear algebra. Experience with machine learning frameworks (TensorFlow or PyTorch) for training, refining, and deploying ML models. Solid understanding of distributed systems, with experience in the Hadoop/Hive ecosystem or other Big Data technologies. Familiarity with cloud platforms like AWS, Azure, and Google Cloud. Proficient in SQL (Spark/Hive SQL) with experience in creating data flows. Experience with version control systems like BitBucket and GIT. Familiar with Agile and Safe frameworks. Cloud AWS experience is a significant plus. Nice to HaveExperience in designing and implementing ML models (e.g., propensity models, customer lifetime value, micro-segmentation) to support training and deployments.