Job Description
Working Student Machine Learning Operations (m/f/d)
Company:
ipoque GmbH
Organizational Unit (R&S):
8IPAA Advanced Techn. Development (IPL)
Job Location:
Leipzig
Career Level:
Working students
Contract Type:
Limited
Full-time / Part-time:
Part-time
ID:
1119
Job Summary
Support us in developing and maintaining our machine learning models! Our young team is currently scaling a high-performance IT infrastructure for computationally intensive ML processes and is looking for you as a working student (m/f/d) to actively support us in our daily operations. By contributing to CI pipelines, JupyterHub, and other systems, you will help reduce downtime, accelerate our development cycles, and assist us in successfully scaling even more robust models in the future.
Tasks
- Support MLOps Engineers in building and maintaining end-to-end ML workflows, from data preparation and model training to testing and deployment
- Assist in setting up and improving reproducible ML training pipelines and experiment workflows
- Help prepare, validate, and manage datasets used for ML model training, evaluation, and testing
- Support the execution, comparison, and documentation of ML model experiments, including relevant metrics and configurations
- Assist in monitoring ML pipelines, model performance, system availability, and resource usage through dashboards
- Perform maintenance and troubleshooting tasks for ML-related IT systems such as JupyterHub, CI pipelines, and compute environments
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Qualifications
- Strong interest in understanding end-to-end ML processes in practice and contributing to different parts of the ML pipeline
- Motivated to build reliable, robust, and well-structured IT and MLOps processes, with a fundamental interest in understanding how systems work
- Analytical problem-solving skills, attention to detail, and the ability to identify areas for improvement
- Good programming skills, preferably in Python, and ideally experience from practical programming projects
- Experience with Linux server administration; knowledge of Docker or virtualization is a plus
- Nice to have: basic knowledge of Machine Learning, Grafana or dashboarding tools, GitLab CI/CD pipelines, or Kubernetes
- Open and proactive communication style, including willingness to ask questions, seek support, and collaborate with the team
Contact and further information
We welcome your application! Submissions are preferred online via the application portal. For questions, our chatbot Paul and the recruiting team are available at any time.
Rohde & Schwarz promotes equal opportunities and welcomes applications from people with and without disabilities. We offer an inclusive work environment where all individuals can develop their skills and talents regardless of gender, nationality, ethnic and social background, religion, worldview, age, sexual orientation, identity, and other characteristics.