Machine Learning Engineer / MLOps Engineer

About the Position

We are looking for an experienced Machine Learning Engineer / MLOps Engineer to help build, deploy, and maintain robust machine learning solutions in production. This is a hybrid role based in Lisbon, ideal for someone with strong Python skills, solid MLOps experience, and hands-on knowledge of cloud environments, CI/CD, containerisation, and model deployment.

Responsibilities

• Collaborate closely with Data Scientists and Engineers to align models, data, and operational workflows.
• Build, deploy, and maintain ML pipelines and production-ready model-serving solutions.
• Implement CI/CD processes to support reliable and repeatable deployments.
• Write clean, testable, reusable, and well-structured Python code for machine learning applications.
• Manage model versioning, optimisation, and deployment across cloud environments.
• Develop and maintain APIs for model inference using FastAPI or Flask.
• Deploy models using Docker or Kubernetes.
• Support model optimisation and compression activities.
• Troubleshoot production issues and take ownership of operational fixes.
• Apply version control, pull requests, code reviews, and ML-specific versioning practices.
• Continuously improve ML engineering and MLOps practices as technologies and standards evolve.

Requirements

• 3+ years of professional experience in Machine Learning.
• Strong Python skills, including project structuring, reusable and testable code, object-oriented programming, and design patterns.
• Experience with Python testing frameworks such as pytest or unittest.
• Strong SQL skills for querying and manipulating data to support model development.
• Experience with machine learning frameworks such as TensorFlow, PyTorch, and Scikit-learn.
• Experience or familiarity with AWS, Google Cloud, or Azure for running and integrating machine learning workloads.
• Experience building and maintaining CI/CD pipelines using GitHub Actions or Jenkins.
• Solid understanding of MLOps fundamentals, including Git versioning, pull requests, code reviews, and ML-specific versioning practices.
• Experience deploying models using Docker or Kubernetes.
• Knowledge of model optimisation and compression.
• Experience building model-serving APIs using FastAPI or Flask.
• Strong troubleshooting and problem-solving skills.
• Ability to work collaboratively and take ownership of operational deliverables.

Nice to Have

• Basic knowledge of Java or Scala for integration with existing systems.

We Offer

• Gross annual salary: €21,000–€26,000, depending on experience and suitability for the role.
• Meal allowance.
• Flexible benefits package.
• Extra day off on your birthday.
• One additional day off on either 24 December or 31 December.

About the Company

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