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Distributed Cloud | AI/Machine Learning Engineer

Porto, Porto, Portugal

Pay
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Employment
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Apply at Devoteam

What you’ll work on

Full posting
  • Design, develop, and implement end-to-end Machine Learning pipelines for training, testing, and deployment of predictive models.

  • Work closely with Data Scientists to translate prototypes and models into scalable, production-grade code (MLOps).

  • Develop robust, efficient, and well-documented code primarily using Python and relevant ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn).

From the employer’s posting
Key Responsibilities Design, develop, and implement end-to-end Machine Learning pipelines for training, testing, and deployment of predictive models. Work closely with Data Scientists to translate prototypes and models into scalable, production-grade code (MLOps).
Design, develop, and implement end-to-end Machine Learning pipelines for training, testing, and deployment of predictive models. Work closely with Data Scientists to translate prototypes and models into scalable, production-grade code (MLOps). Develop robust, efficient, and well-documented code primarily using Python and relevant ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
Work closely with Data Scientists to translate prototypes and models into scalable, production-grade code (MLOps). Develop robust, efficient, and well-documented code primarily using Python and relevant ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn). Implement monitoring and alerting solutions for models in production to track performance, detect drift, and ensure reliability.

What you’ll bring

All qualifications

Core experience

  • 3+ years of professional experience in a Machine Learning Engineer, AI Developer, or similar role.
  • Strong expertise in Python and object-oriented programming, with a focus on code quality and best practices.
  • Solid understanding of MLOps principles and the tools required for model deployment, versioning, and lifecycle management (e.g., MLflow, Kubeflow, or similar).
  • Proficiency in SQL and experience working with large datasets and data warehousing concepts.
  • Experience working with Cloud platforms (AWS, GCP, or Azure) for model deployment, compute, and storage (e.g., SageMaker, Vertex AI, Azure ML Services).
  • Knowledge of containerization technologies (Docker, Kubernetes) for building reproducible and scalable ML environments.
Qualification wording
3+ years of professional experience in a Machine Learning Engineer, AI Developer, or similar role.
Strong expertise in Python and object-oriented programming, with a focus on code quality and best practices.
Solid understanding of MLOps principles and the tools required for model deployment, versioning, and lifecycle management (e.g., MLflow, Kubeflow, or similar).
Proficiency in SQL and experience working with large datasets and data warehousing concepts.
Experience working with Cloud platforms (AWS, GCP, or Azure) for model deployment, compute, and storage (e.g., SageMaker, Vertex AI, Azure ML Services).
Knowledge of containerization technologies (Docker, Kubernetes) for building reproducible and scalable ML environments.
Education & alternatives
- Familiarity with distributed computing frameworks (e.g., Spark). - Advanced degree (M.S. or Ph.D.) in Computer Science, Engineering, or a related quantitative field. - Very good level of English, both spoken and written, for effective communication with international teams;

Tools in this posting

  • Python
  • SQL
  • AWS
  • Azure
  • Docker
  • Google Cloud (GCP)
  • Kubernetes
  • MLflow
  • SageMaker
  • PyTorch
  • TensorFlow
  • Spark
  • scikit-learn
Source — Tool mentions in context
- Work closely with Data Scientists to translate prototypes and models into scalable, production-grade code (MLOps). - Develop robust, efficient, and well-documented code primarily using Python and relevant ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn). - Implement monitoring and alerting solutions for models in production to track performance, detect drift, and ensure reliability.
- 3+ years of professional experience in a Machine Learning Engineer, AI Developer, or similar role. - Strong expertise in Python and object-oriented programming, with a focus on code quality and best practices. - Mandatory practical experience with major Machine Learning frameworks (e.g., TensorFlow, PyTorch) and libraries (e.g., scikit-learn).
- Solid understanding of MLOps principles and the tools required for model deployment, versioning, and lifecycle management (e.g., MLflow, Kubeflow, or similar). - Proficiency in SQL and experience working with large datasets and data warehousing concepts. - Excellent analytical and problem-solving skills, with the ability to communicate complex technical concepts effectively.
- Excellent analytical and problem-solving skills, with the ability to communicate complex technical concepts effectively. - Experience working with Cloud platforms (AWS, GCP, or Azure) for model deployment, compute, and storage (e.g., SageMaker, Vertex AI, Azure ML Services). - Knowledge of containerization technologies (Docker, Kubernetes) for building reproducible and scalable ML environments.
- Experience working with Cloud platforms (AWS, GCP, or Azure) for model deployment, compute, and storage (e.g., SageMaker, Vertex AI, Azure ML Services). - Knowledge of containerization technologies (Docker, Kubernetes) for building reproducible and scalable ML environments. - Familiarity with distributed computing frameworks (e.g., Spark).
- Mandatory practical experience with major Machine Learning frameworks (e.g., TensorFlow, PyTorch) and libraries (e.g., scikit-learn). - Solid understanding of MLOps principles and the tools required for model deployment, versioning, and lifecycle management (e.g., MLflow, Kubeflow, or similar). - Proficiency in SQL and experience working with large datasets and data warehousing concepts.
- Strong expertise in Python and object-oriented programming, with a focus on code quality and best practices. - Mandatory practical experience with major Machine Learning frameworks (e.g., TensorFlow, PyTorch) and libraries (e.g., scikit-learn). - Solid understanding of MLOps principles and the tools required for model deployment, versioning, and lifecycle management (e.g., MLflow, Kubeflow, or similar).
- Knowledge of containerization technologies (Docker, Kubernetes) for building reproducible and scalable ML environments. - Familiarity with distributed computing frameworks (e.g., Spark). - Advanced degree (M.S. or Ph.D.) in Computer Science, Engineering, or a related quantitative field.

Job description

View original posting ↗

Job Description

We are seeking a versatile and passionate AI / Machine Learning Engineer to join our data science and engineering team. You will be instrumental in bridging the gap between data science research and production-ready applications, building scalable machine learning systems that drive business value. This role requires a strong balance of software engineering principles and ML expertise.

Key Responsibilities

  • Design, develop, and implement end-to-end Machine Learning pipelines for training, testing, and deployment of predictive models.
  • Work closely with Data Scientists to translate prototypes and models into scalable, production-grade code (MLOps).
  • Develop robust, efficient, and well-documented code primarily using Python and relevant ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
  • Implement monitoring and alerting solutions for models in production to track performance, detect drift, and ensure reliability.
  • Collaborate with Data Engineers to ensure efficient data preparation, feature engineering, and access to necessary data infrastructure.
  • Stay current with the latest advancements in AI, ML techniques, and scalable infrastructure.

Qualifications

  • 3+ years of professional experience in a Machine Learning Engineer, AI Developer, or similar role.
  • Strong expertise in Python and object-oriented programming, with a focus on code quality and best practices.
  • Mandatory practical experience with major Machine Learning frameworks (e.g., TensorFlow, PyTorch) and libraries (e.g., scikit-learn).
  • Solid understanding of MLOps principles and the tools required for model deployment, versioning, and lifecycle management (e.g., MLflow, Kubeflow, or similar).
  • Proficiency in SQL and experience working with large datasets and data warehousing concepts.
  • Excellent analytical and problem-solving skills, with the ability to communicate complex technical concepts effectively.
  • Experience working with Cloud platforms (AWS, GCP, or Azure) for model deployment, compute, and storage (e.g., SageMaker, Vertex AI, Azure ML Services).
  • Knowledge of containerization technologies (Docker, Kubernetes) for building reproducible and scalable ML environments.
  • Familiarity with distributed computing frameworks (e.g., Spark).
  • Advanced degree (M.S. or Ph.D.) in Computer Science, Engineering, or a related quantitative field.
  • Very good level of English, both spoken and written, for effective communication with international teams;

Additional Information

The Devoteam Group works for equal opportunities, promoting its employees based on merit and actively fights against all forms of discrimination. We are convinced that diversity contributes to the creativity, dynamism and excellence of our organization. All of our vacancies are open to people with disabilities.

Company Description

At Devoteam, we believe that technology with strong human values can actively drive change for the better. Discover how Tech for People unlocks the future, creating a positive impact on the people and the world around us. We are a global leading player in Digital Transformation for leading organisations across EMEA, with a revenue of €1B. We believe in transforming technology to create value for our clients, partners and employees in a world where technology is developed for people. We are proud of the culture we have built together. We are proud of our people at the service of technology. We are proud of our diverse environment. Because we are #TechforPeople. Join our multidisciplinary team of Cloud experts, Designers, Business consultants, Security experts, Engineers, Developers and other extraordinary talents, spread across more than 20 EMEA countries. Become one of our +10.000 tech and business leaders on cloud, data and cyber security. Let’s fuse creativity with technology together and build innovative solutions that actively change things for the better.

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Location & working pattern

Porto, Porto, Portugal

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Status in our records
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First seen by us
May 13, 2026
Recorded sightings
382
Last seen by us
Oct 11, 2026
Employer says posted
Dec 24, 2025

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