Machine Learning and Recommendation Systems Researcher

Job Title: Machine Learning Operations and Computer Vision Researcher

Job Ref: AICOS_Jobs_2022_11

Job Type: Full time contract.

Job Salary: Depending on the academic degree and professional experience of the candidate.

Job Location: Porto, Portugal.


Job Description:

Fraunhofer Portugal AICOS is looking for a researcher specialized in Machine Learning Operations and Computer Vision to join the Intelligent Systems Group.

Researcher positions are highly strategic for Fraunhofer Portugal AICOS’s quest to create scientific knowledge capable of generating added value for its clients and partners. As a researcher at AICOS, you will create purposeful technology to promote economic growth, social well-being and improve the quality of life of its end-users.


Your responsibilities:

- Research and develop computer vision algorithms for image quality and adequacy assessment, object detection, and image classification;

- Research and implement machine learning / deep learning models for data classification capable to learn over time;

- Deploy the developed models to cloud and edge platforms;

- Deliver summarized reports about the developed models and provide proper software documentation.


Academic Qualifications:

Academic Master’s degree or equivalent academic qualifications (or equivalent second cycle complete) in the area of Electrical and Computers Engineering, or related studies.



- Excellent programming skills (C/C++ and Python preferred);

- Demonstrated Machine Learning background, with relevant hands-on experience in computer vision approaches for object detection and image classification;

- Experience in programming with widespread ML Frameworks (e.g., Sklearn, TensorFlow, Keras, PyTorch);

- Excellent English communication skills (technical and business audiences).


We value:

- In-depth knowledge of machine learning pipelines and data product journey (data collection, data labelling, data preparation, model development, model evaluation, model optimization, model deployment and model monitoring);

- Knowledge of productization technologies such as (REST) APIs and Docker containers;

- Knowledge of version control of code, data, and models;

- Ability to work with cross-functional teams;

- Autonomous, dependable, and enthusiast team-player;

- Problem-solving, proactive, and critical-thinking attitude.


In return, we offer:

- Excellent work conditions in a stimulating and dynamic environment with opportunities to contribute to a number of innovation topics and application areas;

- Opportunity to grow in your technical field and make a difference in creating AI solutions that generate value and impact;

- Excellent conditions of employment including attractive salary (depending on the academic degree and professional experience), private health insurance plan, access to entrepreneurship programmes and a people-centric environment.


Why should you join Fraunhofer Portugal:

Operating at the interface between science, research and industry, Fraunhofer offers a broad spectrum of professional opportunities and a working environment that encourages creativity and the development of new ideas, in which personal and career development go hand in hand.


Application Process:

Applications are permanently open until the ideal candidate is selected. A first “cut-off” to evaluate applications day will occur on the 30th of October 2022.

The selected candidate is expected to start working in November 2022.

Applications must be made to the email and contain:

- CV – mandatory;

- Motivation Letter;

- Recommendation Letters are optional but also welcome.



The research activities in the scope of this job opportunity are planned to be developed within the framework of projects:

- Microeletrónica – Agenda Microeletrónica, with reference C644916358 -00000028;

- NewGenTSFAE, – New Generation Test Systems for Future Automotive Electronics, with reference POCI-01-0247-FEDER-046990;

- SmartColor4Ceramics – Smart Color Replication for Ceramics, with reference POCI-01-0247-FEDER-069890.