Machine Learning Engineer

Loop Future; Lisboa; Híbrido; EUR 50 000 - 75 000; Tempo integral

Resumo da oferta

Loop Future is building an international tech hub in Lisbon and seeks a Mid Machine Learning Engineer to bring ML solutions into production, focusing on reliability, monitoring, and collaboration with our data science team.

This hands-on role requires building from scratch without mature MLOps infrastructure, documenting processes, and delivering pragmatic, production-ready pipelines for model deployment in a hybrid Lisbon setting.

Qualificações

• Experience in the machine learning field for 3+ years.
• Proficiency in Python and SQL for ML workflows.
• Experience with cloud platforms (AWS/GCP/Azure) for ML workloads.
• Experience building and maintaining CI/CD pipelines (GitHub Actions, Jenkins).
• Experience with ML frameworks (TensorFlow, PyTorch, Scikit-learn).
• Experience deploying models with Docker or Kubernetes.
• Experience building model-serving APIs (FastAPI or Flask).
• Strong collaboration with data scientists and engineers.
• Strong communication and ownership of deployments.
• English at least B2 level.

Responsabilidades

• Monitor and optimize production ML models and pipelines.
• Deploy models from data scientists into production.
• Build and maintain ML CI/CD deployment pipelines.
• Develop and support ML-focused API services (FastAPI/Flask).
• Collaborate with data scientists and data engineers on deployment.
• Ensure reliability, monitoring, and documentation of ML systems.
• Proactively communicate progress and blockers.

Conhecimentos

Cloud platforms

CI/CD pipelines

Python

SQL

MLOps basics

ML frameworks

Docker/Kubernetes

APIs (FastAPI/Flask)

English B2

3+ years ML

Collaboration

Communication

Ferramentas

GitHub Actions

Jenkins

PyTest

Docker

Kubernetes

Descrição da oferta de emprego

Work setup: Hybrid in Lisbon, 2 days per week in the office.

About Loop Future

Loop Future combines technology, innovation, and sustainability to create digital solutions that shape the future. By integrating software engineering, cloud solutions, salesforce expertise, and intelligent sourcing, Loop Future connects people, systems, and industries — driving efficiency, growth, and global impact. We are Headquartered in Portugal but we are also supported by our international offices in the UK, Switzerland and India. The company brings together a diverse and talented team committed to delivering cutting-edge digital experiences into domains such as TV & Media, Satellite & Space, Consultancy, Retail and many other domains.

About Role

For an international Tech Hub emerging from Lisbon, we're looking for a Mid Machine Learning Engineer to help bring machine learning solutions into production, ensuring reliability, monitoring, documentation, and close collaboration with our data science team. As we build our MLOps practice from the ground up, you'll play a key role in turning models into scalable, production-ready systems.

This is a hands-on, builder-focused role. We don't yet have sophisticated MLOps infrastructure in place, so you'll help create solutions from scratch, including manual model deployments before automation is introduced. We value people who understand when a pragmatic solution is the right one, work effectively without heavy processes, and take ownership of what they build.

Responsibilities

• Monitoring and alerting
• Production performance optimization
• Retraining automation initiatives
• Productionize ML models - Reliably deploy models developed by data scientists into production environments.
• Build and maintain deployment pipelines — Develop and support ML-focused CI/CD pipelines.
• Monitor models in production - Track performance, failures, and key metrics, implementing basic alerting where needed.
• Write quality, maintainable code - Produce clean, structured, testable Python code aligned with team standards.
• Collaborate cross-functionally - Work closely with data scientists and data engineers on model deployment and data transformation initiatives.
• Optimize performance - Improve model response times and operational efficiency in production environments.

Requirements

• Familiarity with AWS, GCP, or Azure for running and integrating ML workloads
• Experience building and maintaining CI/CD pipelines using tools such as GitHub Actions or Jenkins
• Strong Python skills, including project structuring, reusable and testable code, object-oriented programming, design patterns, and testing frameworks (pytest/unittest)
• Strong SQL skills for querying and manipulating data in support of model development
• Understanding of MLOps fundamentals, including Git versioning, pull requests, code reviews, and ML-specific versioning practices
• Experience with core ML frameworks, including TensorFlow, PyTorch, and Scikit-learn
• Experience deploying models with Docker or Kubernetes, including an understanding of model optimization and compression
• Familiarity with building model-serving APIs using FastAPI or Flask
• Nice to have: Basic knowledge of Java or Scala for integrating with existing systems
• Strong collaborator who works effectively with data scientists and engineers to align models, data, and operations
• Proactive communicator who clearly shares progress, blockers, and support needs
• Solid problem-solver capable of handling moderately complex technical challenges with appropriate guidance
• Takes ownership and accountability for operational deliverables, including pipelines, deployments, and production fixes
• Learns quickly and adapts based on technical feedback and evolving best practices
• More than 3 years of experience in the Machine Learning field.
• English proficiency should be at least B2 level.