Machine Learning Engineer

Shalion

. Own the end-to-end lifecycle of ML systems, with focus on deployment and monitoring .

Posted 10/22/2026full-timeBarcelona • SpainJuniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and deploying Machine Learning systems, with a strong focus on Python programming, clean code practices, and CI/CD workflows. Capable of transforming research into production-ready solutions while ensuring maintainability and scalability.

Highest-signal resume keywords

Machine Learning Systems DeploymentPython Software EngineeringCI/CD WorkflowsModel Development LifecycleContainerization (Docker)

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningPythonModel ProductionizationCode RefactoringTesting Best PracticesModel VersioningData Flow ManagementCloud Environments (AWS)Data Platforms (Snowflake)CI/CD

Soft Skills

Pragmatic Problem-SolvingSolution-Oriented MindsetAdaptability in Ambiguous EnvironmentsAttention to DetailTeam Collaboration

Tools & Technologies

DockerAWSSnowflake

Industry Keywords

Machine Learning LifecycleProduction EnvironmentsClean Code PracticesModular CodeData Engineering

Tech Stack

Tools & technologies

AWSCloudDockerPython

About the role

Key responsibilities & impact

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, and 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
Transform research-driven work into robust, production-ready systems that deliver business impact

Requirements

What you’ll need

1+ years of experience building and deploying ML systems in production environments
Strong software engineering skills in Python, with a focus on writing clean, maintainable, and testable code
Proven experience taking models from notebook to production
Solid understanding of the model development lifecycle
Familiarity with containerization (Docker) (bonus)
Experience with cloud environments (AWS preferred) and data platforms such as Snowflake (bonus)
Pragmatic and solution-oriented
Comfortable working in ambiguous environments and bringing structure where needed
Quality-driven mindset with attention to maintainability and long-term scalability

Benefits

Comp & perks

Hybrid work model – 3 days in-office, 2 days remote
Flexible benefits – allocate part of your gross salary (pre-tax) to meal vouchers, transport allowance, and private healthcare at a preferential rate
Fresh fruit and specialty coffee daily
International team with colleagues from 10+ nationalities
Dynamic and innovative environment
Impactful work on a challenging and innovative project
Permanent contract