Working Student Software Engineer (Automation & ML)
Role details
Job location
Tech stack
Job description
Systems Engineering Networking Cloud CAN Solid NumPy UI Entwicklungsumgebungen Policy Automatisierung Programmiererfahrung Software-Engineering IT REST across Boosting Übersetzungssoftware Scikit-learn Python Docker GIT CSV MS Excel CS Engineering, Do you get a thrill from making a boring Excel workflow disappear behind a single command? Want to ship ML powered tools that real engineers use-cutting hours on internal processes and boosting accuracy? If you're a Bachelor's level SWE who loves turning experiments into usable products, this role is for you.
Join our Systems Engineering & Innovation team to automate manual, time consuming workflows, build internal tools and services, apply ML/AI where it adds clear value, and deliver measurable improvements in speed and quality.
What you'll do
- Map existing workflows; identify and prioritize high impact automation opportunities.
- Build robust scripts/services for data ingestion, validation, parameter generation, and reporting.
- Integrate with planning tools and data sources via APIs and common formats (CSV/Excel); manage lightweight data stores as needed.
- Prototype and operationalize ML models (e.g., classification, recommendations, anomaly detection, optimization heuristics); track metrics and impact., * APIs, Ablaufplanung, Algorithmus, Automatisierung, Cloud Computing, Code-Review, Computerprogrammierung, Datenaufnahme, Datenspeicher, Datenverarbeitung, Docker, Erkennung von Anomalien, Experimentieren, Git, Innovation, Künstliche Intelligenz, Mathematik, Metriken, Microsoft Excel, Numpy, Pandas, Prototyping, Python, Pytorch, ReactJS, Reproduzierbarkeit, Restful APIs, SQL, Scikit-learn, Softwareentwicklung, Systems Engineering, Telekommunikation, Testen, Workflows
Schulabschluss
- Bachelor
Sprachkenntnisse
Requirements
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Enrolled in a bachelor's program (CS/EE/Math or similar) with at least one shipped project or substantial system.
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Strong programming skills (Python preferred) and solid software engineering fundamentals (Git, testing, code reviews).
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Practical ML/AI experience (scikit learn and/or PyTorch or similar); able to move from notebook to a usable tool.
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Automation and data wrangling experience (Pandas/NumPy, SQL), working with REST APIs and CSV/Excel.
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Clear, confident English; additional EU languages are a plus. Nice to have
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Exposure to networking/telecom, graph algorithms, or optimization (NetworkX, OR Tools).
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Lightweight UI for internal tools (Streamlit/Dash or simple React) and CLI tooling (Typer/Click).
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Containers for reproducibility (Docker). Cloud experience is not required.