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.

• 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

• 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

• 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.