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.

Machine Learning Engineer

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