Applied Machine Learning Engineer, Industry Solutions
Munich, Germany; St Gallen, Switzerland
R
CHF 63K-69K (estimate) Entry-level Full Time
Tasks
- Build and deliver machine learning solutions for industrial clients
- Build training and evaluation pipelines
- Conduct statistical significance testing
- Contribute to internal machine learning libraries and SDK
- Design cross validation and baseline models
- Design end-to-end machine learning pipelines
- Engineer features aligned with quantum components
- Evaluate where quantum layer adds measurable benefit
- Implement quantum machine learning algorithms in classical pipelines
- Perform data cleaning and leakage prevention
- Profile and improve training stability
- Select classical machine learning methods for problems
- Treat quantum layer as a constrained component
Perks/Benefits
Skills/Tech-stack
Cirq | Computer Vision | Configuration Management | Cross-validation | Data cleaning | Deep learning | Experiment design | Feature Engineering | Git | Gradient boosting | Hyperparameter Tuning | Kernel methods | Language Processing | Leakage detection | LightGBM | Model Evaluation | Model Training | Natural Language | Natural Language Processing | Neural Networks | NumPy | Pandas | PennyLane | PyTorch | Python | Qiskit | Random Forests | Regularization | Reproducible environments | Scikit-learn | Series forecasting | Statistical Testing | TensorFlow | Testing | Time Series | Time Series Forecasting | Training pipelines | XGBoost
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
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