Production ML Engineer — End-to-End Systems, Hybrid

Shalion; Barcelona; Hybrid; EUR 65,000 - 90,000; Full time

Benefits offered by this job

International team

Hybrid work model

Meal vouchers

Private healthcare

Office in Barcelona

Job summary

Shalion, a data and insights-driven company, is hiring a Machine Learning Engineer in Barcelona. You will join a Data Science team to transform research-driven work into robust, production-ready systems and elevate engineering maturity.

You will deploy, monitor, and productionize models, while collaborating with Data Scientists and Engineers to ensure reliable data flows and well-structured interfaces. The role offers a hybrid model with 3 days in-office and 2 remote.

Qualifications

• Experience building ML systems in production environments.
• Strong software engineering skills in Python with maintainable, testable code.
• Proven experience taking models from notebook to production.
• Solid understanding of model development lifecycle.
• Familiarity with containerization (Docker).
• Experience with AWS and data platforms like Snowflake is a plus.

Responsibilities

• Own the end-to-end lifecycle of ML systems, with focus on deployment and monitoring.
• Refactor and productionize existing models and notebooks into clean, modular, and testable code.
• Introduce and enforce best practices in coding, testing, model versioning.
• Set up and improve CI/CD workflows for ML systems.
• Work closely with Data Scientists and Data Engineers to ensure clean interfaces and reliable data flows.
• Act as a technical reference within the team, reviewing code and guiding less experienced members.

Skills

ML systems production

Python programming

Notebook to production

Model lifecycle understanding

Cloud environments

Docker familiarity

Tools

Docker

AWS

Snowflake

Python

Job description

Shalion, a data and insights-driven company, is hiring a Machine Learning Engineer in Barcelona. You will join a Data Science team to transform research-driven work into robust, production-ready systems and elevate engineering maturity.

You will deploy, monitor, and productionize models, while collaborating with Data Scientists and Engineers to ensure reliable data flows and well-structured interfaces. The role offers a hybrid model with 3 days in-office and 2 remote.