Senior AI/MLOps Engineer - Remote Cloud ML Pipelines Lead

Airswift; España; A distancia; EUR 92.250 - 184.500; Jornada completa

Descripción de la vacante

Airswift is seeking a Senior AI/MLOps Engineer to lead scalable ML infrastructure and production-ready AI systems. This remote role supports a freelance arrangement with a daily rate structure and is open to applicants from Spain, Romania, Bulgaria, Czech Republic, or Slovakia.

The candidate will architect and optimize end-to-end MLOps pipelines, deploy and monitor ML models, and collaborate with data scientists to productionise models using MLflow, Airflow or Dagster.

Formación

• Strong hands-on experience with AWS, Docker, Kubernetes (cloud-native MLOps stack).
• Proven delivery of production ML systems end-to-end (build, deploy, monitor).
• Expertise with MLflow, Airflow or Dagster for pipeline orchestration.
• Experience with Kafka / streaming architectures and data engineering.
• Advanced Python and SQL.
• Strong leadership and stakeholder communication skills.

Responsabilidades

• Lead the architecture and optimisation of end-to-end MLOps pipelines across cloud environments (ideally AWS).
• Drive deployment, monitoring, and scaling of ML models using Docker and Kubernetes.
• Build and maintain batch and real-time inference systems leveraging streaming tools (e.g. Kafka).
• Collaborate closely with Data Scientists to productionise models using MLflow, Airflow or Dagster.
• Provide technical leadership, mentoring engineers, and setting best practices.
• Translate complex ML concepts into business value and influence stakeholders.
• Continuously improve system reliability, performance, and scalability.

Conocimientos

Leadership

Stakeholder communication

Python

SQL

Herramientas

AWS

Docker

Kubernetes

MLflow

Airflow

Dagster

Kafka

Descripción del empleo

Airswift is seeking a Senior AI/MLOps Engineer to lead scalable ML infrastructure and production-ready AI systems. This remote role supports a freelance arrangement with a daily rate structure and is open to applicants from Spain, Romania, Bulgaria, Czech Republic, or Slovakia.

The candidate will architect and optimize end-to-end MLOps pipelines, deploy and monitor ML models, and collaborate with data scientists to productionise models using MLflow, Airflow or Dagster.