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Eqvilent is seeking a middle-level MLOps Engineer to strengthen ML model pipelines and ensure data quality. The role emphasizes a strong Python background and familiarity with MLOps practices.
You will design and build ELT pipelines for data processing and analysis, implement automated MLOps pipelines for retraining and validation, and apply CI/CD practices for smooth model deployment. You will collaborate with an international team and have opportunities for growth.
Eqvilent is seeking a middle-level MLOps Engineer to enhance ML model pipelines and ensure data quality. This role is ideal for candidates with a strong Python background and familiarity with MLOps practices.
As an MLOps Engineer at Eqvilent, you will focus on designing and building ELT pipelines for data processing and analysis, ensuring the integrity of data used for training machine learning models. Your work will involve constructing automated MLOps pipelines for retraining and validating models, as well as implementing CI/CD practices for smooth model deployment.
Success in this position means creating robust monitoring systems to track model performance in production, utilizing tools like Grafana and Prometheus. You will collaborate with a team of international professionals in a supportive environment that values innovation and offers opportunities for personal and professional growth.