ML Engineer: Real-Time AI Systems & MLOps Architect

HappyRobot

España

Presencial

EUR 70.000 - 110.000

Jornada completa

hace 11 horas
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Descripción de la vacante

HappyRobot in Spain is seeking its first ML engineers to design, build, and deploy end-to-end ML systems that power our AI-driven products. You will own the lifecycle from data ingestion to production, shaping the technical direction of our platform.

This role emphasizes MLOps, scalability, and robust pipelines; you will collaborate with product and engineering teams and stay ahead with the latest AI infrastructure, contributing to fast, responsible decisions across real-world applications.

Formación

  • Strong experience in machine learning, deep learning, and NLP.

Responsabilidades

  • Design, build, and maintain scalable ML systems — from data ingestion and preprocessing to training, testing, and deployment.
  • Develop end-to-end ML pipelines (data collection, labeling, training, validation, monitoring) to ensure reliability and reproducibility.
  • Implement robust MLOps practices, including model versioning, CI/CD for ML, and continuous monitoring in production.
  • Collaborate with product and engineering teams to integrate and deploy models into real-time products with a focus on efficiency and scalability.
  • Ensure data quality, observability, and performance across all AI systems.
  • Stay current with the latest in AI infrastructure, tooling, and research — helping us stay ahead of the curve.

Conocimientos

Python
Machine learning
Deep learning
NLP
Data pipelines
Go
MLOps
Data processing

Herramientas

MLflow
Kubeflow
Weights & Biases
Docker
Kubernetes

Descripción del empleo

HappyRobot in Spain is seeking its first ML engineers to design, build, and deploy end-to-end ML systems that power our AI-driven products. You will own the lifecycle from data ingestion to production, shaping the technical direction of our platform.

This role emphasizes MLOps, scalability, and robust pipelines; you will collaborate with product and engineering teams and stay ahead with the latest AI infrastructure, contributing to fast, responsible decisions across real-world applications.

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