MLOps Engineer

Summary

Join our team as an experienced MLOps Engineer and contribute to improving machine learning model training pipelines, data quality processing, model testing and validation, and model monitoring systems. You will design and build ELT pipelines, construct MLOps pipelines for automated retraining, implement CI/CD pipelines for model deployment, and create model monitoring services. The ideal candidate possesses strong Python knowledge, familiarity with Docker, and a basic understanding of machine learning. We offer a welcoming international team, cutting-edge technology, flexible work arrangements (including remote options), and a generous 40 paid days off.

Requirements

• Strong knowledge of Python
• Familiarity with Docker
• Basic understanding of machine learning concepts and techniques

Responsibilities

• Design and build ELT pipelines for data processing and analysis
• Construct MLOps pipelines for automated retraining and validation of models
• Implement CI/CD pipelines for deploying models and ML services
• Create services for monitoring ML models in production

Preferred Qualifications

• Experience with PyTorch
• Familiarity with Kubernetes
• Knowledge of Dagster
• Experience with Kafka
• Understanding of distributed training systems for ML models

Benefits

• Great challenges with many opportunities to prove yourself
• A welcoming group of highly qualified international professionals
• Great corporate culture with internal events and surprising commitment to fostering a supportive and empowering environment
• Cutting-edge hardware and technology
• Comfortable Dubai, London, Malta and Mumbai offices or remotely anywhere in the world
• 40 paid days off
• Competitive salary