ML Engineer (W/M/D)
Tasks
- Analyze large datasets
- Build data pipelines
- Collaborate with data, product, and engineering teams
- Design machine learning models
- Develop APIs and microservices
- Develop and deploy machine learning models
- Expose machine learning models to applications
- Implement CI/CD deployment automation
- Implement MLOps practices
- Monitor model performance
- Perform feature engineering
- Test machine learning pipelines
- Version machine learning models
Perks/Benefits
- Additional paid days off
- Family care policy
- Flexible work environment
- Free yoga lessons
- Health insurance
- Holiday bonus
- Home office equipment support
- Lunch vouchers
- Modern office
- No meeting Wednesday mornings
- Paid child sick days
- Public transport reimbursement
- RTT
- Remote-friendly
- Therapy or coaching sessions
- Training budget
Skills/Tech-stack
APIs | AWS SageMaker | Azure ML | CI/CD | DVC | Data Preprocessing | Docker | Feature Engineering | Google Cloud | Google Cloud Vertex | Google Cloud Vertex AI | Kubeflow | Kubernetes | LightGBM | MLflow | Microservices | Model Monitoring | Model versioning | PyTorch | Python | Reproducibility | SQL | Scikit-learn | TensorFlow | Vertex AI | XGBoost
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