AI/ML Engineer
Tasks
- Adopt generative AI for patient education
- Apply feature engineering techniques
- Build data pipelines for model training and validation
- Collaborate with cross-functional teams to translate clinical needs
- Design supervised machine learning models
- Develop ML risk prediction models
- Develop unsupervised machine learning models
- Ensure model reproducibility and monitoring
- Identify health risks and support personalized interventions
- Implement privacy preserving machine learning practices
- Integrate ML models into production SaMD
- Maintain MLOps infrastructure and development practices
- Train and evaluate machine learning models
- Validate model performance and evaluation metrics
Perks/Benefits
- Europe based candidate preference
- Fully remote
- Healthcare technology environment
- Permanent position
- Remote-first culture
Skills/Tech-stack
Bias Mitigation | Data Pipelines | Data Wrangling | Explainable AI | Feature Engineering | Generative AI | MLOps | Machine Learning | Medical Device | Model Evaluation | Model Validation | Monitoring | Privacy-preserving | Privacy-preserving machine learning | PyTorch | Python | Reproducibility | Scikit-learn | Series modeling | Signal Processing | Software as a Medical Device | Supervised Learning | TensorFlow | Time Series | Time Series Modeling | Unsupervised Learning
Education
N/A
Roles
AI | AI/ML Engineer | Data Scientist | Engineer | Learning Engineer | ML Engineer | Machine Learning Engineer | Scientist
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