Machine Learning Engineer | Mid

Sobre a vaga

This role focuses on bringing machine learning models into production, supporting the creation of pragmatic MLOps practices. You will join an international technology and professional services environment based in Lisbon, ensuring reliable deployment, monitoring, and operational performance.

O que vais fazer

• Deploy machine learning models developed by data science teams into production environments with reliability and operational control
• Build, execute and maintain ML-focused CI/CD pipelines, starting with pragmatic deployment approaches and evolving towards automation
• Monitor production models by tracking performance, failures, key metrics and basic alerts
• Write clean, structured, reusable and testable Python code aligned with team standards
• Collaborate with data scientists and data engineers to align model deployment, data transformation and production operations
• Optimize model response times and operational efficiency in production environments
• Contribute to retraining automation initiatives and the continuous improvement of MLOps practices

O que é pedido

• More than 3 years of experience in machine learning, model deployment or related production engineering work
• Professional working proficiency in English, at least B2 level
• Experience working in hands-on environments where solutions need to be created, documented and improved progressively
• Collaborative profile with the ability to work closely with data science, data engineering and software engineering teams
• Proactive communication, ownership and accountability for deployment, monitoring and production support activities
• Problem-solving ability to address moderately complex technical challenges with appropriate guidance
• Adaptability to feedback, evolving practices and changing technical priorities
• Availability for a hybrid work model in Lisbon
• Python, including project structure, reusable code, object-oriented programming, design patterns and testing practices
• Pytest or unittest
• SQL for querying, transforming and analyzing data
• MLOps fundamentals, including Git versioning, pull requests, code reviews and ML-specific versioning practices
• CI/CD pipelines with tools such as GitHub Actions or Jenkins
• Cloud platforms such as AWS, GCP or Azure for ML workload execution and integration
• Machine learning frameworks such as TensorFlow, PyTorch and Scikit-learn
• Docker or Kubernetes for model deployment
• Model optimization and compression concepts
• API development for model serving using FastAPI or Flask
• Monitoring and alerting practices for production systems

Valorizado

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

O que é oferecido

• Private health insurance from the first day, with no waiting periods and optional family extension
• Confidential and free access to psychological support, content and live sessions through TEAM 24
• Continuous training and certification support to strengthen long-term professional development
• Flexibility whenever the role and context allow it, supporting balance across different life stages
• Childcare vouchers and practical support measures for family life
• Team moments, shared milestones and leadership presence when it matters most
• Upskilling opportunities in quality management, information security, AI governance and cybersecurity best practices

Resumo organizado por IA a partir do anúncio original. Confirma os detalhes no site da empresa.