We help people discover the magic of the perfect tutor, craft a personalised learning journey, and stay motivated to keep growing. Our approach is human-led, tech-enabled - and it’s creating real impact.We’ve just reached unicorn status with a $150M Series D, accelerating our vision to transform education through human-led, AI-enhanced learning. As a category-defining company, we’re shaping what the future of learning looks like at integral scale.Every Preply lesson sparks change, fuels ambition, and drives progress that matters.

Joining

Preply means helping define the future of education at global scale, and building something that truly matters for millions of people, every day.About the roleAs Preply scales its AI-powered learning platform, we’re looking for an experienced Senior ML Platform/Ops Engineer to help productionize machine learning systems with high reliability, performance, and observability.You’ll work at the intersection of ML, data engineering, and cloud infrastructure enabling fast, secure, and reproducible model development from training to deployment.We’ve reached 90%+ adoption of AI coding tools across engineering, and we’re now moving towards more autonomous, AI-Augmented development at scale. You’ll collaborate closely with ML Scientists, Backend Engineers, and Data Engineers to shape the foundations of our ML lifecycle.What you’ll be doingBuild and maintain ML pipelines for training, evaluation, and deployment using tools like Databricks, MLFlow, Airflow, DBT, Sagemaker, TectonSupport 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 teamsEnsure ML services are modular, testable, and monitored from day oneExploration and productionization of LLM-based features (e.g., retrieval pipelines, prompt evaluation, model serving)What we’re looking forProven 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 workflowsUnderstanding of ML model lifecycles: training, validation, deployment, and monitoringStrong 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. Exposure to LLM serving, vector databases, or GenAI-powered product flowsDeep, hands-on expertise in AI tools, especially in agentic AI SDLCWhy you’ll love it at PreplyAn open, collaborative, dynamic and diverse culture;com, Learning & Development budget and time off for your self-development;A competitive financial package with equity, leave allowance and health insurance;Keep perfecting - To create an outstanding customer experience, we focus on simplicity, smoothness, and enjoyment, continually perfecting it as every detail matters.Growth mindset - We proactively seek growth opportunities and believe today's best performance becomes tomorrow's starting point.

Raise the bar - We raise our performance standards continuously, alongside each new hire and promotion. Challenge, disagree and commit - We value open and candid communication, even when we don’t fully agree. We believe that the presence of different opinions and viewpoints is a key ingredient for our success as a multicultural Ed-Tech company.

📌 Machine Learning Engineering (Barcelona)
🏢 Preply
📍 Barcelona