ML Engineer — MLOps & Model Deployment (Hybrid, Porto)

iTRTech Group

Lisboa

Hybrid

EUR 32,000 - 36,000

Full time

33 hours ago
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Job summary

iTRTech Group in Porto is seeking a Mid/Senior Machine Learning Engineer to develop AI solutions across the full lifecycle—from data prep and model training to deployment and retraining, using MLOps practices.

You will collaborate with data scientists and engineers, build proofs-of-concept, and ensure production-ready ML deployments with APIs and robust pipelines. Fluency in English is required.

Qualifications

  • 3–5 years of proven relevant experience in ML engineering.
  • Strong programming skills in Python for ML development.
  • Experience with TensorFlow, PyTorch, or Scikit-learn.
  • Knowledge of data processing and feature engineering techniques.
  • Experience with model deployment, APIs, and MLOps practices.
  • Familiarity with Azure ML, Snowflake, and dbt; SQL and data pipelines.
  • Experience working with Agile methodologies (Scrum/Kanban).

Responsibilities

  • Develop ML solutions covering data preparation, feature engineering, training, deployment, and retraining.
  • Train and refine AI models with practical business applications.
  • Collaborate with Data Scientists and Data Engineers to define technical requirements.
  • Build proof-of-concept/value solutions using modern AI frameworks.
  • Maintain AI solutions following DevOps and MLOps principles.
  • Share knowledge and support handover of new AI concepts to the data community.

Skills

Python
ML frameworks
Data processing
MLOps
APIs

Tools

TensorFlow
PyTorch
Scikit-learn
Azure ML
Snowflake
dbt
SQL

Job description

iTRTech Group in Porto is seeking a Mid/Senior Machine Learning Engineer to develop AI solutions across the full lifecycle—from data prep and model training to deployment and retraining, using MLOps practices.

You will collaborate with data scientists and engineers, build proofs-of-concept, and ensure production-ready ML deployments with APIs and robust pipelines. Fluency in English is required.

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