Machine Learning Engineer

Equação IT is a company focused on boosting technology and solid solutions through our expert consultants leading a high perspective and adding value to our customers with the purpose of providing optimization and business growth to our partners.

About the Role

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.


What You'll Own

Deployment pipeline execution
Production model management
Monitoring and alerting
Production performance optimization
Retraining automation initiatives


Key Responsibilities

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.


Technical Skills

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


Professional Skills

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


Expected experience:

More than 3 years of experience in the Machine Learning field.
English proficiency should be at least B2 level.

Duration: Long Term Contract.
Location: Lisbon
Work model: hybrid with at least 2 days at the office