Job Description

Machine Learning Engineer – Lisbon (hybrid)

#TeamCandour are working with our international financial services client to add another Machine Learning Engineer to join their award winning Data team in Lisbon.

This role offers a unique opportunity to work at the intersection of machine learning, software engineering, and cloud infrastructure. You will play a pivotal role in building and maintaining the infrastructure that supports the deployment of machine learning models, contributing to cutting-edge solutions within the industry.

Responsibilities:

As a Machine Learning Engineer, your key responsibilities will include:

• Developing and maintaining infrastructure for deploying machine learning models in real-time and batch environments.
• Building and maintaining Python APIs (Flask/FastAPI) to serve machine learning models.
• Collaborating with cross-disciplinary teams to integrate machine learning services into user-facing applications.
• Aligning with platform engineers to ensure scalable and efficient deployments.
• Reviewing pull requests and contributing to code quality across the team.
• Monitoring and maintaining cloud-based machine learning services to ensure reliability and performance.
• Designing and implementing CI/CD pipelines for machine learning model deployment.
• Writing unit tests and adhering to object-oriented programming principles for maintainable code.
• Supporting data modeling and cloud networking tasks as needed.
• Enhancing the model registry, including tracking, upgrading, and monitoring machine learning models.

Qualifications

• A Bachelor's or Master's degree in a quantitative field (e.g., Computer Science, Statistics, Mathematics, Physics, Engineering) or equivalent experience.
• Proven hands-on experience in machine learning engineering, including deploying, monitoring, and maintaining models in production environments.
• Solid experience as a Python developer, particularly in a machine learning engineering context.
• Strong understanding of software engineering best practices, including test-driven development (TDD).
• Proficiency with infrastructure-as-code tools like Terraform.
• Hands-on experience with cloud platforms such as GCP, AWS, or Azure.
• Familiarity with containerization using Docker and orchestration of deployments.
• Experience with CI/CD tools and Git-based development workflows.
• Understanding of API operations, monitoring, and logging.
• Strong problem-solving skills and the ability to work independently on technical tasks.
• Familiarity with Agile methodologies and experience working in Agile teams.

Day-to-Day

Your daily activities will include:

• Writing clean, reusable, and efficient Python code to support machine learning model deployment.
• Collaborating with data scientists, platform engineers, and developers to ensure seamless integration of machine learning solutions.
• Monitoring and optimizing cloud-based machine learning services for performance and reliability.
• Participating in Agile development cycles, including sprint planning, stand-ups, and retrospectives.
• Reviewing code and providing constructive feedback to maintain high-quality standards.
• Designing and maintaining CI/CD pipelines to streamline the deployment process.
• Troubleshooting and resolving technical issues related to machine learning infrastructure.

If you are curious and want to run through the finer details of what could be YOUR ideal next career move, reach out today!