MACHINE LEARNING ENGINEER - MODEL DEVELOPMENT & MLOPS (HYBRID)

iTRTech Group; Lisboa; Hybrid; EUR 32,000 - 36,000; Full time

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

MACHINE LEARNING ENGINEER - MODEL DEVELOPMENT & MLOPS (HYBRID PORTO)

Portuguese company hires for hybrid position.

Location: Porto, Portugal

Only candidates already based in Portugal will be considered.

Work Model: Hybrid — 2 days per week in the office

Language Requirements: Fluent English required.

Seniority: Mid/Senior (3-5 years)

Rate Between €2900 - 3200 RV or unipessoal (gross value).

About The Opportunity

We are looking for a Machine Learning Engineer to develop and maintain AI solutions throughout the full lifecycle, from data preparation and model training to deployment, retraining, and production operations using MLOps practices.

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 and proof-of-value solutions using modern AI frameworks.
• Maintain and improve AI solutions following DevOps and MLOps principles.
• Share knowledge and support the handover of new AI concepts to the data community.

Requirements

• 3–5 years of proven relevant experience.
• Strong programming skills in Python or similar languages 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.
• Working knowledge of SQL and data pipelines.
• Experience working with Agile methodologies such as Scrum or Kanban.

Ideal Candidate Profile

An analytical and detail-oriented engineer who can connect model development with production requirements. Strong collaboration and communication skills, curiosity about emerging AI technologies, and the ability to manage competing priorities are essential.

5 Questions for Candidates

• Do you have 3–5 years of relevant experience developing and delivering machine learning solutions?
• Which ML frameworks have you used, and what models have you trained or refined?
• What experience do you have with data preparation, feature engineering, SQL, and data pipelines?
• How have you deployed, operated, and retrained models using MLOps practices?
• Are you fluent in English and available to work on-site in Porto 2 days per week?

Keywords

Machine Learning Engineer, Python, TensorFlow, PyTorch, Scikit-learn, Feature Engineering, Model Training, Model Deployment, Retraining, MLOps, DevOps, APIs, Azure ML, Snowflake, dbt, SQL, Data Pipelines, Proof of Concept, Proof of Value, Agile.