Descripción del trabajo
Build the Data and Machine Learning Foundation Behind Every Doodle Product
Doodle is a B2B SaaS platform used by millions of professionals to coordinate meetings and collaboration. Reliable data infrastructure and well operated machine learning systems are essential to building secure, intelligent, and scalable products for our customers.
As a Data Infrastructure & MLOps Engineer, you will design, build, and operate the platforms that enable data engineering, analytics, and machine learning across Doodle. Working closely with product, engineering, data, and security teams, you will make data easier to access, models easier to deploy, and systems easier to monitor and maintain.
What You Will Do
As a Data Infrastructure & MLOps Engineer, you will own the reliability, scalability, and automation of Doodle's data and machine learning platforms.
Data Infrastructure & Platform Engineering
- Design, build, and operate scalable data infrastructure for ingestion, transformation, storage, and serving.
- Develop reliable batch and streaming data pipelines that support product analytics, business intelligence, and machine learning use cases.
- Establish data platform standards for performance, availability, observability, documentation, and cost management.
- Improve data discoverability and usability through data cataloguing, lineage, ownership, and quality processes.
Machine Learning Operations
- Build and maintain MLOps workflows covering experimentation, data and model versioning, training, evaluation, deployment, and rollback.
- Operate machine learning workloads in production, including model serving, feature pipelines, scheduled retraining, and inference infrastructure.
- Partner with data scientists and software engineers to turn prototypes into reliable, maintainable production services.
- Introduce repeatable approaches for model validation, monitoring, drift detection, performance measurement, and incident response.
Cloud Infrastructure & Au
📌 Data Infrastructure (Madrid)
🏢 Doodle
📍 Madrid