Machine Learning Engineer

Alongside; Porto; Híbrido; EUR 60 000 - 90 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Hybrid work model

International environment

Exposure to modern technologies

Resumo da oferta

Alongside, a Portuguese company partnering with international organizations to build and scale tech teams, seeks a Machine Learning Engineer for a client project. You will design and deploy end-to-end ML pipelines, APIs, and MLOps, collaborating with data scientists and operating in an Agile/Scrum setting.

Ideal candidates have 5+ years in Backend or ML engineering, strong Python skills, and hands-on experience deploying ML models with AWS SageMaker, Docker, and Kubernetes.

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 E2E ML pipelines and deploying ML models through APIs.
• 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.
• Fluent English and strong communication and technical decision-making skills.

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

Backend engineering

ML deployment

AWS SageMaker

Docker & Kubernetes

Formação académica

BSc in Computer Engineering

Ferramentas

MLflow

Kubeflow

TensorFlow

PyTorch

SQL/NoSQL

Descrição da oferta de emprego

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