MLOps Engineer

Responsibilities:

• Collaborate with Data Scientists, MLOps engineers and business stakeholders to understand requirements and translate them into scalable data and ML solutions
• Design, build and maintain robust data pipelines for ML model training and inference using structured and unstructured data of various scale
• Develop and maintain production-ready code for training, serving, and monitoring machine learning models
• Implement CI/CD pipelines deployment and retraining workflows
• Ensure reproducibility and traceability of ML experiments using versioning and metadata tools
• Monitor performance and health of deployed models

Requirements:

• Fluent in Python
• Familiarity with software engineering principles, including unit testing and version control (e.g., Git)
• Familiarity with Linux-based environments and scripting for automation
• Experience monitoring ML models in production, including logging, metrics, and alerting
• Experience in working with Kubernetes
• Experience with Microsoft Azure; nice to have experience deploying ML solutions in cloud environments (e.g., Microsoft Azure, AWS, or GCP)
• Minimum of 3 years of experience in a data science, data engineering, ML engineering or MLOps engineering role
• Bachelor’s or Master’s degree in Computer Science, Mathematics, Engineering, or a related field
• Knowledge and experience with Vector DBs
• Understanding and experience in working with CI/CD tools
• Understanding and experience in working with CI/CD tools
• Knowledge of machine learning techniques and model lifecycle management
• Knowledge of methods and techniques for explaining decisions of ML models

Offer:

• Private medical care (dental care + vision care plan)
• Life insurance
• Sports card
• Training & learning opportunities
• Language course co-financing
• Annual bonus
• Employee referral program