Senior ML Platform & MLOps Engineer

Preply; United States; Remote; USD 180,000 - 270,000; Full time

Job summary

Preply is seeking an experienced Senior ML Platform/Ops Engineer to productionize ML systems with high reliability, performance, and observability. You’ll work at the intersection of ML, data engineering, and cloud infrastructure enabling fast, reproducible model development from training to deployment.

You’ll collaborate with ML Scientists, Backend Engineers, and Data Engineers to shape the ML lifecycle, scale pipelines, and advance AI-enabled development across our platform.

Qualifications

• Five+ years of experience deploying ML systems in production.
• Strong Python and SQL skills with experience in orchestration tools.
• Proficient in modern cloud platforms (GCP or AWS), Kubernetes, and CI/CD workflows.
• Knowledge of ML model lifecycles: training, validation, deployment, and monitoring.
• Experience with DevOps practices in ML environments.

Responsibilities

• Build and maintain ML pipelines for training, evaluation, and deployment.
• Support reproducible, containerized model training environments and scale compute.
• Define observability and alerting for ML systems.
• Design and scale data ingestion and feature transformation flows.
• Contribute to internal libraries and tooling for model experimentation and deployment.
• Ensure ML services are modular, testable, and monitored from day one.
• Explore and productionize LLM-based features and retrieval pipelines.

Skills

Python

SQL

CI/CD

DevOps

ML production

Tools

Databricks

MLFlow

Airflow

DBT

Sagemaker

Kubernetes

Kubeflow

Dagster

Spark

BigQuery

GCP

AWS

Tecton

Job description

Preply is seeking an experienced Senior ML Platform/Ops Engineer to productionize ML systems with high reliability, performance, and observability. You’ll work at the intersection of ML, data engineering, and cloud infrastructure enabling fast, reproducible model development from training to deployment.

You’ll collaborate with ML Scientists, Backend Engineers, and Data Engineers to shape the ML lifecycle, scale pipelines, and advance AI-enabled development across our platform.