Senior Machine Learning Engineer

About this role

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.