MLOps Engineer @ Square One Resources

Approximately 5+ years of experience in the role of Machine Learning Engineer / MLOps Engineer / ML Engineer Very good knowledge of Python and the data science ecosystem Experience in building and deploying ML models into production Practical experience with AWS SageMaker Knowledge of at least one deep learning framework (TensorFlow or PyTorch) Experience in MLOps: MLflow (tracking, model registry) Experience in CI/CD (GitLab) Ability to design and describe the architecture of ML systems Experience working with cloud systems (AWS preferred) We are looking for two experienced engineers to join a team developing a globally deployed recommendation system. The system already generates significant business value in many countries, and now we are entering a phase of its further evolution and professionalization in the area of MLOps and scaling. This is a role for individuals who want to genuinely influence the architecture of production ML systems and co-create work standards for data science and ML engineering teams. [Design and development of the production recommendation system architecture, Building and developing MLOps standards within the organization, Creating and optimizing CI/CD pipelines in GitLab, Implementation and development of the MLflow process (experiment tracking, model versioning), Deploying ML models into production on AWS SageMaker, Collaboration with Data Scientists on model productionization, Building solutions ensuring monitoring, observability, and reliability of models, Active programming in Python (data/ML infrastructure, deployment, pipelines), Mentoring and technical support for Data Scientists and engineers, Collaboration with Product Owners and business stakeholders]