AI/ML Engineer
Tasks
- Apply privacy preserving machine learning
- Build data pipelines for model deployment
- Build data pipelines for model testing
- Build data pipelines for model training
- Build data pipelines for model validation
- Contribute to MLOps process improvements
- Deploy machine learning models
- Design supervised machine learning models
- Design unsupervised machine learning models
- Develop machine learning solutions for risk prediction
- Develop personalized intervention models
- Enable adaptive care pathways
- Ensure model explainability
- Ensure model privacy
- Ensure regulatory compliance
- Evaluate generative AI for digital coaching
- Evaluate generative AI for healthcare education
- Evaluate machine learning models
- Implement model monitoring
- Integrate machine learning models into production
- Optimize model performance
- Perform data preparation
- Perform feature engineering
- Perform model validation
- Perform real world signal processing
- Train machine learning models
- Validate machine learning models
Perks/Benefits
Skills/Tech-stack
Bias Mitigation | Data Pipelines | Data Wrangling | Explainable AI | Feature Engineering | Generative AI | MLOps | Machine Learning | Medical Device | Model Monitoring | Model Validation | Privacy-preserving | Privacy-preserving machine learning | PyTorch | Python | Regulated Healthcare | Reproducibility | Scikit-learn | Signal Processing | Software as a Medical Device | TensorFlow | Time Series
Education
N/A
Roles
AI | AI Engineer | Engineer | Learning Engineer | Machine Learning Engineer
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