Staff Machine Learning Scientist
Tasks
- Apply model interpretability techniques
- Build machine learning models for molecular signal detection
- Collaborate with computational biologists and molecular biologists
- Collaborate with machine learning engineers to optimize model training
- Communicate cross disciplinary research results
- Design and drive research experiments
- Develop early blood based cancer detection algorithms
- Fine-tune deep learning models
- Train models for high accuracy and robust generalization
Perks/Benefits
Skills/Tech-stack
AWS | Artificial Intelligence | Automated Regression | Automated regression testing | Azure | Boosting | Cloud Computing | Contrastive Learning | Decision Trees | Deep learning | Deployment Automation | Docker | Docker containers | Foundation Models | GCP | Generalized Linear Models | Hugging Face | JAX | Kernel methods | Language Models | Large Language Models | Linear Models | MLflow | Machine Learning | Model Interpretability | Model aggregation | Neural Networks | PyTorch | Python | Random Forests | Regression testing | Self-Supervised Learning | Self-supervised | Statistical modeling | Supervised Learning | TensorBoard | TensorFlow | Version control | Weights and Biases
Education
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