We power people’s progress.
At Preply, we’re all about creating life-changing learning experiences. 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. Today, 100,000+ tutors teach 90+ languages to learners in 180 countries — and we’re only getting started. As a category-defining company, we’re shaping what the future of learning looks like at global 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 role
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)
What we’re looking for
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
Why you’ll love it at Preply
Open, collaborative, dynamic and diverse culture.
Generous monthly allowance for lessons on Preply.com .
Learning & Development budget, including time off for your self-development.
Competitive financial package with equity, and leave allowance.
Opportunity to shape the lives of learners and tutors from over 175 countries through language learning and teaching.
Our Principles
Care to change the world — We are passionate about our work and care deeply about its impact to be life-changing.
We do it for learners — For both Preply and tutors, learners are why we d
