Senior Machine Learning Engineer

Alongside; Porto; Híbrido; EUR 70 000 - 100 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Hybrid working model

Resumo da oferta

Alongside, a Portuguese company partnering with international organizations to build and scale exceptional tech teams, is seeking a Senior Machine Learning Engineer in Porto. You will design and maintain scalable data and end-to-end ML pipelines, deploy ML services and APIs, and work with AWS SageMaker in containerized environments.

The role emphasizes MLOps, CI/CD, and agile delivery in a hybrid office model.

Qualificações

• 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 end-to-end 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.
• Experience with Docker and Kubernetes.

Responsabilidades

• 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.

Conhecimentos

Python

ML pipelines

AWS SageMaker

Docker/Kubernetes

MLOps

SQL/NoSQL

API deployment

GIT/CI-CD

English communication

Formação académica

Degree in Computer Engineering/IT or related field

Ferramentas

MLflow

Kubeflow

Descrição da oferta de emprego

Alongsideis 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.

Qualifications & 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.

Hybrid Working Model:

• 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.