Senior Machine Learning Engineer
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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 . 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.
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