We are seeking a Junior MLOps Engineer to design, build, and maintain the infrastructure and tools that enable our data science and machine learning teams to develop, deploy, and monitor production ML systems at scale. You will bridge the gap between data science and operations, ensuring reliable, efficient, and reproducible ML workflows.

Key Responsibilities:

ML Pipeline & Automation:

• Create CI/CD pipelines for ML model training, validation, and deployment
• Implement automated model retraining and versioning systems
• Build orchestration workflows for data processing and model training
• Develop automated testing frameworks for ML models and pipelines

Monitoring & Operations:

• Implement model monitoring systems for performance, drift, and data quality
• Set up logging, alerting, and observability for ML systems
• Establish model governance and compliance tracking
• Create dashboards for model performance and infrastructure metrics
• Develop incident response procedures for production ML systems

Collaboration & Best Practices:

• Partner with data scientists and AI engineers to productionize ML models
• Establish MLOps best practices and standards across teams
• Provide technical guidance on deployment architecture
• Document processes, systems, and runbooks

Required Qualifications:

Education:

• Bachelor's degree in Computer Science, Engineering, or related field (or equivalent experience)
• Master's degree preferred but not required with sufficient practical experience

Experience:

• 1+ year working as ML/Software/DevOps Engineer
• Proven track record of building production ML systems at scale

Technical Skills:

• Intermediate proficiency in Python
• Good understanding of containerization (Docker, Kubernetes)
• Some experience with CI/CD tools (Jenkins/GitLab CI/GitHub Actions/etc.)
• Some experience with workflow orchestration (Airflow/Kubeflow/Prefect, etc.)

Core Competencies:

• Basic understanding of ML lifecycle and model development processes
• Linux/Unix systems administration skills
• Some experience with version control systems (Git) and branching strategies
• Knowledge of microservices architecture and API design

Soft Skills:

• Strong problem-solving and debugging abilities
• Excellent communication skills with both technical and non-technical stakeholders
• Ability to work independently and manage multiple priorities
• Collaborative mindset with emphasis on enabling others
• Adaptability to rapidly changing technology landscape
• Pragmatic approach to balancing innovation with reliability

We offer:

• 5/2, 09.00-18.00/ 08:00-17:00;
• Meal allowance;
• Annual performance bonuses;
• Corporate health program: VIP voluntary insurance and special discounts for gyms;
• Access to Digital Learning Platforms

Note: Only candidates who meet the requirements of the vacancy will be contacted for the next stage.

Interested candidates can send their CV to the e-mail address in the Apply for job button.