Mid Machine Learning Engineer
Summary
Mid-level Machine Learning Engineer who takes ML models from development into production: building CI/CD pipelines for ML workloads, monitoring model performance, automating retraining/deployment, and helping stand up the company's MLOps practice from scratch. Core stack: Python, SQL, AWS/GCP/Azure, Docker/Kubernetes, FastAPI/Flask, TensorFlow/PyTorch. Hybrid: 2 days/week in the Lisbon office.
We’re looking for a Mid Machine Learning Engineer to help bring Machine Learning models into production and make sure they run reliably and efficiently.
You’ll work closely with Data Scientists and Data Engineers, taking models from development into real-world production environments.
As we’re building our MLOps practice from the ground up, you’ll have the opportunity to help shape how we deploy, monitor and manage ML models. This is a hands-on role where you’ll have real ownership and the chance to build solutions from scratch.
What You’ll Do
- Deploy and manage Machine Learning models in production.
- Build and maintain CI/CD pipelines for ML workloads.
- Monitor model performance, failures and key metrics.
- Implement monitoring and basic alerting solutions.
- Write clean, maintainable and testable Python code.
- Work closely with Data Scientists and Data Engineers.
- Improve model performance and production response times.
- Help automate model retraining and deployment processes.
- Contribute to the development of our MLOps practices and infrastructure.
What We’re Looking For
- 3+ years of experience in Machine Learning.
- Strong Python skills.
- Good SQL knowledge.
- Experience with at least one cloud platform: AWS, GCP or Azure.
- Experience with CI/CD, such as GitHub Actions or Jenkins.
- Good understanding of MLOps fundamentals, including Git, pull requests, code reviews and versioning.
- Experience with ML frameworks such as TensorFlow, PyTorch or Scikit-learn.
- Experience deploying models using Docker and/or Kubernetes.
- Experience building APIs with FastAPI or Flask.
- Understanding of testing practices and frameworks such as pytest or unittest.
- Ability to work closely with technical teams and communicate clearly.
- Proactive mindset, ownership and willingness to learn.
- English B2 or higher.
Nice to Have
- Knowledge of Java or Scala.
- Experience with model optimization or compression.
- Previous experience working with MLOps platforms or production ML environments.
Work model: 2 days per week in the office (in Lisbon) and 3 days at home.