Machine Learning Engineer: Build Scalable AI in Production

Fyld; Portugal; On-site; EUR 55,000 - 85,000; Full time

Job summary

Fyld, a Portuguese consulting company, is hiring a Machine Learning Engineer to design, deploy and optimize scalable ML solutions. You will work across data science and engineering teams to translate business needs into robust models and production-ready pipelines.

The role emphasizes technical rigor, MLOps practices, cloud platforms, and building APIs, with opportunities to grow in a values-driven environment that prioritizes transparency and collaboration.

Qualifications

• Bachelor's or Master's degree in Computer Science, AI, Data Science, Mathematics, or related fields.
• Strong programming skills in Python.
• Experience developing and deploying ML models with scikit-learn, TensorFlow or PyTorch.
• Experience building scalable ML pipelines and production-ready solutions.
• Knowledge of MLOps practices and tools such as MLflow, Kubeflow or similar.
• Experience with cloud ML platforms (Azure ML, AWS SageMaker or Google Vertex AI).
• Experience with Docker, Kubernetes and CI/CD pipelines is valued.
• Familiarity with feature engineering, model evaluation and monitoring.
• Experience integrating ML models into APIs or backend applications.
• Knowledge of SQL and data processing techniques.
• Fluency in English.

Responsibilities

• Design, deploy and optimize machine learning solutions.
• Develop scalable ML pipelines and production-ready systems.
• Integrate ML models into APIs or backend applications.
• Apply MLOps practices and monitor model performance.
• Collaborate with data, product and engineering teams.

Skills

Python

ML model development

ML deployment

ML pipelines

MLOps

Cloud platforms

Docker

Kubernetes

API integration

SQL

English

Education

Bachelor's or Master's in CS/AI/DS/Math

Tools

MLflow

Kubeflow

Docker

Kubernetes

CI/CD

AWS SageMaker / Azure ML / Vertex AI

Job description

Fyld, a Portuguese consulting company, is hiring a Machine Learning Engineer to design, deploy and optimize scalable ML solutions. You will work across data science and engineering teams to translate business needs into robust models and production-ready pipelines.

The role emphasizes technical rigor, MLOps practices, cloud platforms, and building APIs, with opportunities to grow in a values-driven environment that prioritizes transparency and collaboration.