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Senior Machine Learning Engineer

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Hybrid

Senior Machine Learning Engineer

Alongside

Senior Machine Learning Engineer

Skills

SQL QueriesDockerPythonpandasPyTorchTensorFlowMachine LearningAWSKubernetesNLP / Natural Language ProcessingComplianceTerraform

1 month ago

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Important information


Contract type:

Permanent

Location:

Porto, Portugal

Work mode:

Hybrid

Published on:

17 September 2026

What they need


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

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