ML Engineer - End-to-End AI & MLOps Expert

team.it; Porto; On-site; EUR 50,000 - 80,000; Full time

Benefits offered by this job

Health insurance

Life insurance

Discounts and perks

Telecommunications plan

Job summary

team.it is seeking a Machine Learning Engineer in Porto to design and manage the full ML lifecycle, from data prep to production monitoring. You will collaborate with data scientists and engineers to deliver scalable AI solutions and drive modernization through MLOps.

Strong experience (3–5 years) in ML engineering and proficiency in Python and major ML frameworks is required, with hands-on cloud experience (Azure ML/Snowflake/dbt) and solid SQL skills.

Qualifications

• 3–5 years of proven ML engineering experience.
• Strong Python and ML frameworks (TF, PyTorch, scikit-learn).
• Experience with end-to-end ML lifecycle and MLOps.
• Experience with cloud platforms: Azure ML, Snowflake, dbt.

Responsibilities

• Design, implement, and maintain the full machine learning lifecycle, including data preparation, feature engineering, model training, validation, deployment, and retraining.
• Ensure operation, monitoring, and continuous improvement of AI solutions through MLOps practices.
• Collaborate with Data Scientists and Data Engineers to define requirements and build scalable AI solutions.
• Develop and operationalize proof-of-concept initiatives using state-of-the-art AI frameworks.
• Support deployment and maintenance of AI models in production environments for reliability and performance.
• Promote knowledge sharing and adoption of emerging AI technologies across the organization.
• Drive continuous improvements in ML engineering processes, tooling, and delivery practices.

Skills

Python

TensorFlow

PyTorch

Scikit-learn

Data preprocessing

MLOps

SQL

Tools

Azure ML

Snowflake

dbt

Job description

team.it is seeking a Machine Learning Engineer in Porto to design and manage the full ML lifecycle, from data prep to production monitoring. You will collaborate with data scientists and engineers to deliver scalable AI solutions and drive modernization through MLOps.

Strong experience (3–5 years) in ML engineering and proficiency in Python and major ML frameworks is required, with hands-on cloud experience (Azure ML/Snowflake/dbt) and solid SQL skills.