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.