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 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.