Machine Learning Engineer/ MLOps at Bridge 351
Portugal
Posted
on-site · full_time · Visa sponsorship
Apply for this role at Bridge 351
Responsibilities:
- Productionize ML models: deploy and manage models developed by data scientists into reliable production environments.
- Build and maintain ML CI/CD pipelines and deployment automation (GitHub Actions, Jenkins, etc.).
- Monitor models in production: track performance, failures, and key metrics; implement alerting and retraining triggers.
- Optimize model performance and inference latency; implement model compression or serving improvements.
- Write clean, testable Python code and build model-serving APIs (FastAPI/Flask).
- Collaborate with data scientists and data engineers on data transformation, feature pipelines, and deployment requirements.
- Maintain containerized deployments using Docker/Kubernetes and support orchestration in cloud environments.
Requirements:
- More than 3 years of experience in the ML field (production-facing MLOps or ML engineering).
- English proficiency at least B2; work model includes 2 days/week in the Lisbon office.
- Strong Python skills, project structuring, and testing (pytest/unittest).
- Solid SQL skills for data querying and preparation.
- Experience with CI/CD tooling and ML-focused pipelines.
- Familiarity with cloud platforms (AWS, GCP, or Azure) and deploying ML workloads there.
- Experience with TF/PyTorch/Scikit-learn and serving models in containers or Kubernetes.
- Knowledge of model monitoring, versioning, and retraining automation patterns.
- Nice to have: basic Java or Scala for integration with existing systems.