Junior MLOps Researcher (Job Ref: AICOS_Jobs_2024_07) - Porto

Junior MLOps Researcher (Job Ref: AICOS_Jobs_2024_07)
Porto
Porto, Porto District, Portugal

Organisation/Company: Associação Fraunhofer Portugal Research

Department: R&D

Research Field: Computer science » Programming Engineering » Electrical engineering

Researcher Profile: First Stage Researcher (R1)

Positions: Master Positions

Country: Portugal

Application Deadline: 15 Mar 2025 - 23:59 (Europe/Lisbon)

Type of Contract: Other

Job Status: Full-time

Hours Per Week: 40

Offer Starting Date: 1 Apr 2025

Is the job funded through the EU Research Framework Programme? Not funded by a EU programme

Reference Number: AICOS_Jobs_2025_07

Is the Job related to staff position within a Research Infrastructure? Yes

Offer Description

Job Title: Junior MLOps Researcher

Job Ref. : AICOS_Jobs_2025_07

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 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
- edge research and
- world impact. You will contribute to initiatives that enhance industries, promote social
- 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/Min
  IO;
- Parse
  - defined,
  - 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
  - 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. ,
  - learn, Tensor
  Flow, Keras, Py
  Torch);
- Experience with, or willingness to learn, cloud computing, particularly AWS;
- Experience with, or willingness to learn,
  -
  - 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 Min
  IO 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
- functional teams;
Autonomous, dependable, proactive, and a
- thinking team player.

Why should you join Fraunhofer Portugal:

Innovative Environment: Be part of a
- centric workplace that fosters creativity and
-
-
- 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
- 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
- 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.