MLOps Engineer improving training pipelines and model performance for Eqvilent. Responsible for implementing CI/CD and monitoring systems in a remote work environment.
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.
Requirements
Strong knowledge of Python
Familiarity with Docker
Basic understanding of machine learning concepts and techniques
Experience with PyTorch (a plus)
Knowledge of Dagster (a plus)
Experience automating ML pipelines from data ingestion to deployment with monitoring and observability (a plus)
Experience with monitoring frameworks (Grafana, Prometheus, or similar) (a plus)
Understanding of distributed training systems for ML models (a plus)
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
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