Machine Learning Platform/Ops Engineer
Role details
Job location
Tech stack
Job description
- Build and maintain ML pipelines for training, evaluation, and deployment.
- Support AI scientists in creating reproducible, containerized model training environments.
- Define and implement observability and alerting for ML systems.
Conocimientos
Python SQL Airflow Kubernetes CI/CD Machine Learning Systems DevOps Practices
Herramientas
Databricks MLFlow DBT Sagemaker Spark Kafka Descripción del empleo We power people's progress., As 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. At Preply, engineers have direct access to the best tools available, with the freedom to use them fully and experiment as they build.
You'll collaborate closely with ML Scientists, Backend Engineers, and Data Engineers to shape the foundations of our ML lifecycle. What you'll be doing
- 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)
Requirements
Preply is seeking a Senior ML Platform/Ops Engineer based in Bellprat, Spain to scale its AI-powered learning platform. The ideal candidate will have over 5 years of experience in designing and deploying ML systems. Responsibilities include building ML pipelines, supporting AI scientists, and implementing observability for ML systems. The role offers a collaborative environment and benefits including a competitive financial package, health insurance, and a generous allowance for learning opportunities., * 5+ years of proven experience designing and deploying ML systems in production.
- Proficiency in Python and SQL, and orchestration tools.
- Strong understanding of modern cloud platforms (GCP or AWS), Kubernetes, and CI/CD workflows., * 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
- Deep, hands-on expertise in AI tools, especially in agentic AI SDLC
Benefits & conditions
Generous monthly allowance for lessons on Preply.com Competitive financial package with equity Health insurance Access to free mental health support, Why you'll love it at Preply
- An open, collaborative, dynamic and diverse culture;
- A generous monthly allowance for lessons on 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;
- The opportunity to unlock the potential of learners and tutors through language learning and teaching in 175 countries (and counting!)