Project information: Industry: banking Rate: up to 170 zł/h net + VAT Location: Gdańsk, Gdynia, Warsaw, or Łódź Hybrid role: 40% remote, 60% onsite Summary: The primary objective of the Senior Data/ML Engineer role is to oversee the complete lifecycle of machine learning models and enhance MLOps practices to deliver high-quality machine learning solutions. This includes development, deployment, and monitoring to ensure optimal performance and reliability within the organization.Main Responsibilities: Manage the lifecycle of machine learning models from development to deployment and monitoring. Implement MLOps principles, including continuous integration, continuous delivery, testing, and monitoring. Work with Spark & Python to maintain data ingestions and transformations, handling real-time and batch data processing. Build distributed and highly parallelized big data processing pipelines for massive data in near real-time. Leverage Spark for data enrichment and transformation to enable advanced analytics. Collaborate with cross-functional teams to deliver machine learning solutions. Develop analytics models in partnership with analysts and stakeholders. Optimize MLOps practices and explore cloud solutions in AI/ML areas. Key Requirements: Minimum 5 years proficiency in Python & Spark. Hands-on experience with AWS services (S3, Glue, SageMaker, Lambda). Practical understanding of AWS Infrastructure and automation using CLI, boto3, and IAM roles. Understanding of algorithms, data structures, statistics, and linear algebra. Experience with machine learning frameworks (TensorFlow or PyTorch). Solid understanding of distributed systems (Hadoop/Hive ecosystem). Proficient in SQL (Spark/Hive SQL). Experience with code versioning tools (BitBucket, GIT). Familiar with Agile/Safe framework. Nice to Have:Design and implementation of ML Models (e.g., Propensity, Customer Lifetime Value).