Junior MLOps Engineer

Job Title: Junior MLOps Engineer

Job Ref: AICOS_Jobs_2025_07

Job Type: Full-time contract.

Job Location: Porto, Portugal.

 

Job Description and Responsibilities:

Fraunhofer Portugal AICOSis seeking a talented Junior MLOps Engineer to join our dynamic and multidisciplinary team within the Intelligent Systems group. In this role, you will be at the forefront of technological innovation, working on applied research projects that bridge the gap between cutting-edge research and real-world impact. You will contribute to initiatives that enhance industries, promote social well-being, and improve quality of life. Specifically, you will contribute to the development of a robust and flexible ML backend for a platform aiming to support the development and deployment of traceable and auditable ML pipelines.

 

Your role:

- Contribute to the development of a MLOps Backend:

> Handle data transfer and metadata storage using Metaflow with S3/MinIO;

> Parse user-defined, configuration-based ML pipelines into Metaflow pipelines;

> Integrate with MLFlow for experiment tracking and model registry.

- Infrastructure Management:

> Streamline infrastructure deployment using Terraform and HELM;

> Automate configuration for execution on specified compute providers, including Kubernetes clusters (on-premises or cloud-based – e.g., AWS).

- Module Registry Development:

> Develop a module registry for Python code modules that integrates with the existing backend.

- Collaboration and Maintenance:

> Maintain and improve the current codebase;

> Collaborate with other engineers to further develop the overall platform.

 

Your profile:

- Academic Qualifications: Master’s degree or equivalent qualifications in Computer Science, Electrical and Computer Engineering, or related studies.

- Technical Skills:

> Proficient in writing Python code;

> Experience with, or willingness to learn, microservices and containerization technologies like Docker and Kubernetes;

> General knowledge of machine learning workflows and frameworks (e.g., scikit-learn, TensorFlow, Keras, PyTorch);

> Experience with, or willingness to learn, cloud computing, particularly AWS;

> Experience with, or willingness to learn, infrastructure-as-code tools like Terraform;

> Familiarity with, or willingness to learn, MLOps tools such as Kubeflow, Metaflow, MLFlow, or similar.

> Knowledge of, or willingness to learn, storage solutions like S3 and MinIO for data transfer and metadata storage.

- Other skills:

> Excellent English communication skills (technical and general audiences).

 

We value:

- Expertise or high interest in hosting and scaling ML pipelines in production environments;

- Ability to work effectively in multidisciplinary and cross-functional teams;

- Autonomous, dependable, proactive, and a critical-thinking team player.

 

Why should you join Fraunhofer Portugal:

- Innovative Environment: Be part of a people-centric workplace that fosters creativity and out-of-the-box thinking. We encourage the development of new ideas and ensure that every voice is heard;

- Research with Impact: Engage in projects that sit at the intersection of research and real-world applications, contributing to technology that makes a tangible difference in society;

- Multidisciplinary Teams: Collaborate with professionals from diverse backgrounds, enhancing your learning and professional growth;

- Professional Excellence: Work within a culture that upholds professional standards and best practices, promoting continuous improvement and excellence in research;

- Flexible Work Arrangements: Benefit from flexible working hours and opportunities to work from home, supporting a healthy work-life balance;

- Comprehensive Benefits: Benefit from a partially funded health insurance plan, and a variety of additional perks;

- Supportive Culture: Join a team with an excellent spirit, where collaboration, mutual support, and team achievements are celebrated.

 

Application Process:

Apply through the form down below, including your Curriculum Vitae (mandatory).

Applications are permanently open until the ideal candidate is selected. 

The selected candidate is expected to start working in May 2025.  

 

Note:

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

- ACHILLES – Human-centred Machine Learning: Lighter, Clearer, Safer, with Notice No. HORIZON-CL4-2024-DATA-01-01 and Project Reference No. 101189689;

- NextGenAI – Center for Responsible AI, with Notice No. 01/C05-i01/2021 and Project Reference No. 62 - C645008882-00000055;

- AICeBlock – AI Certification through the Blockchain.