Machine Learning Engineer

Alongside is a Portuguese company that partners with international organizations to build and scale exceptional tech teams. We are looking for a Senior Machine Learning Engineer to join a project with one of our clients, a global leader in professional information solutions and software. Operating across more than 180 countries, the company develops technology-driven solutions for industries including Healthcare, Tax & Accounting, Financial & Corporate Compliance, and Legal & Regulatory . Responsibilities: Design, develop, and maintain scalable data and end-to-end ML pipelines , from data ingestion to production deployment. Build and deploy ML services and APIs , ensuring reliability, scalability, and performance. Partner with Data Scientists to transform models into robust, production-ready solutions. Implement MLOps best practices , including CI/CD, testing, data/code quality, monitoring, and model lifecycle management. Troubleshoot production ML systems and drive technical and architectural decisions. Work with AWS ML services , particularly SageMaker, and containerized environments using Docker/Kubernetes. Contribute to GenAI implementations within our platform framework. Mentor team members and contribute to delivery in an Agile/Scrum environment . Requirements Degree in Computer Engineering, IT, or a related field. 5+ years of experience in Backend Engineering and/or Machine Learning Engineering. Strong production-level Python development skills. Hands-on experience building E2E ML pipelines and deploying ML models through APIs. Experience with SQL/NoSQL databases , testing frameworks, and data/code quality practices. Experience with MLOps tools such as MLflow, Kubeflow, or similar. Strong knowledge of AWS , particularly SageMaker and related ML services. Experience with Docker and Kubernetes . Strong understanding of ML model deployment and lifecycle management. Fluent English and strong communication and technical decision-making skills. Nice to Have Experience with Computer Vision, NLP, TensorFlow/PyTorch, Scikit-Learn, Pandas, Terraform/CloudFormation, asynchronous messaging , and ML monitoring/observability tools. Benefits Hybrid working model: 2 days per week at the office (Porto); Collaborative and international work environment; Opportunity to work on impactful software products and transformation projects; Exposure to modern technologies, tools, and development practices; Opportunity to collaborate with experienced professionals across different countries and areas of expertise.