preply - Senior Machine Learning Platform/Ops Engineer
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Requirements
• Proven experience designing and deploying ML systems in production (5+ years in relevant roles) • Proficiency in Python and SQL, and orchestration tools (Airflow, Kubeflow, Dagster, etc.) • Experience with modern cloud platforms (preferably GCP or AWS), Kubernetes, and CI/CD workflows • Understanding of ML model lifecycles: training, validation, deployment, and monitoring • Strong DevOps practices: Git, IaC (Terraform), logging/observability, containerization (Docker/K8s) • Ability to work independently with ML Scientists and mentor peers in reliability, testing, and delivery. Product impact driven. • Exposure to LLM serving, vector databases, or GenAI-powered product flows
Responsibilities
• Build and maintain ML pipelines for training, evaluation, and deployment using tools like Databricks, MLFlow, Airflow, DBT, Sagemaker, Tecton • Support AI scientist creating reproducible, containerized model training environments (on-demand and scheduled), and manage compute at scale (e.g., spot/GPU autoscaling) • Define and implement observability and alerting for ML systems (model drift, data quality, feature coverage, etc.) • Design and scale data ingestion and feature transformation flows using batch (e.g., Spark/BigQuery) and streaming (Kafka or equivalent) • Contribute to internal Python libraries and platform tooling that accelerate experimentation and deployment for all model teams • Ensure ML services are modular, testable, and monitored from day one • Exploration and productionization of LLM-based features (e.g., retrieval pipelines, prompt evaluation, model serving)
Benefits
• An open, collaborative, dynamic and diverse culture; • A generous monthly allowance for lessons on Preply.com http://preply.com/, Learning & Development budget and time off for your self-development; • A competitive financial package with equity, leave allowance and health insurance; • Access to free mental health support platforms;
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