Senior MLOPS Engineer

Senior Machine Learning / MLOps Engineer responsible for scaling, operating, and evolving production-grade machine learning systems with a strong focus on reliability, automation, and best engineering practices. Your responsibilities: • Lead the design and evolution of a large-scale, production recommender system • Own architectural decisions ensuring scalability, performance, and reliability • Build and maintain end-to-end ML pipelines in a cloud environment • Define and implement MLOps standards, tooling, and best practices • Develop and optimize CI/CD pipelines for ML workflows using GitLab • Ensure model reproducibility, versioning, and experiment tracking with MLflow • Deploy, monitor, and operate ML models on AWS SageMaker • Collaborate with data scientists to productionize machine learning models • Improve system observability, monitoring, and model performance • Provide technical mentorship and architectural guidance to ML and data teams • Contribute hands-on to a Python-based ML and data infrastructure codebase • Translate business and product requirements into technical ML solutions We are looking for you, if you have: • Bachelor’s degree in Computer Science, Engineering, or equivalent practical experience • 5+ years of experience in machine learning engineering or MLOps roles • Proven experience building and operating production ML systems at scale • Strong expertise in Python and the ML/data ecosystem • Hands-on experience with AWS SageMaker in production environments • Experience with deep learning frameworks such as PyTorch or TensorFlow • Solid understanding of MLOps practices including CI/CD and model lifecycle management • Practical experience using MLflow for experiment tracking and model management • Experience designing and maintaining CI/CD pipelines with GitLab • Strong background in cloud-based ML architectures, preferably on AWS • Experience mentoring engineers and collaborating across multidisciplinary teams • Ability to clearly communicate complex technical concepts to diverse stakeholders We offer: • Participation in interesting and demanding projects • Flexible working hours • A great, non-corporate atmosphere • Stable employment conditions (contract of employment or B2B contract) • Opportunities for development and promotion • Attractive package of benefits • Work model: remote or hybrid (2 days per week from the office) We reserve the right to contact the selected candidates.