Make an impact by working for sectors where technology is the enabler, everything is ground-breaking and there’s a constant need to be innovative.

Create and enhance projects in Java, Python, Angular, PHP, .NET and so much more while diving in the world of Blockchain, Artificial Intelligence, Data Science, Security and Internet of Things.

Be part of the team that combines business knowledge, technological edge and a design experience. Our different backgrounds and know-how are key in developing solutions and experiences for digital clients.

Face challenges and learn other ways of thinking and seeing the world - there’s always room for your energy and creativity.

About the role

As a Machine Learning Engineer, you will design, build, and deploy end-to-end ML solutions in production. You will work closely with data scientists and engineers to develop scalable data pipelines, experiment with algorithms, manage the ML lifecycle with tools like MLflow, and ensure reliable deployment and monitoring of models.

As a part of your job, you will:

• Design, develop, train, and optimize machine learning models using modern frameworks.
• Build and maintain scalable data processing pipelines for data ingestion, transformation, and preparation.
• Implement and manage ML workflows using model tracking/versioning tools such as MLflow or similar.
• Create and maintain containerized environments for model deployment (e.g., Docker, Kubernetes).
• Collaborate with engineering and data science teams to integrate ML solutions into production systems.
• Monitor, evaluate, and continuously improve model and pipeline performance.

What are we looking for?

• A degree in an analytical field (e.g., Computer Science, Engineering, Mathematics, Statistics, or a similar domain).
• Minimum of 2 years of experience as a Machine Learning Engineer or in a similar role.
• Strong proficiency in Python.
• Hands-on experience with ML frameworks such as Keras, PyTorch, and scikit-learn.
• Experience with MLflow or equivalent model management tools.
• Experience with PySpark and large-scale data processing.
• Experience in containerization (Docker, Kubernetes, or similar).

Nice to have:

• Experience with Kubeflow or similar MLOps platforms.
• Knowledge of CI/CD best practices applied to machine learning pipelines.

Personal traits

• Ability to adapt to different contexts, teams, and Clients;
• Teamwork skills but also a sense of autonomy;
• Motivation for international projects and ok if travel is included;
• Willingness to collaborate with other players;
• Strong communication skills.
  

At Celfocus, we are committed to cultivate a diverse and inclusive workplace. As an equal-opportunity employer, we welcome applicants of all backgrounds, gender identities, and abilities. We are dedicated to providing reasonable accommodations for candidates with specific needs. If you require any adjustments during the selection process, please inform our Talent Acquisition Team.

Come join the Team!