Job Description and Responsibilities:

Fraunhofer Portugal AICOS is seeking a talented 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:

• Develop and Enhance MLOps Backend:

> Continue developing our MLOps backend, focusing on security in and scalability;

> Integrate with tools for experiment tracking and model storage.

• Infrastructure Management:

> Handle data transfer and metadata storage;

> Streamline infrastructure configuration and deployment for clients (including Kubernetes clusters).

• Module Registry Development:

> Contribute to the development of a module registry for Python code modules that integrate 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 microservices and containerization technologies like Docker and Kubernetes (or willingness to learn);

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

> Experience in cloud computing, particularly AWS;

> Experience with infrastructure-as-code tools like Terraform;

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

> Knowledge of 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 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;
• 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:

Applications are permanently open until the ideal candidate is selected. A first "cut-off" to evaluate applications day will occur on the 27th of November 2024.

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

Applications must be made to the email [email protected] and contain:

• CV – mandatory;
• Motivation Letter;
• Recommendation Letters are optional but also welcome.

Observation:

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

• ACHILLES – Human-centred Machine Learning: Lighter, Clearer, Safer, with Notice No. HORIZON-CL4-2024-DATA-01-01 and reference XYZ;
• NextGenAI – Center for Responsible AI, with Notice No. 01/C05-i01/2021 and reference Projeto nº 62 – C645008882-00000055.