Staff Machine Learning Scientist, Translational AI
Tasks
- Author technical manuscripts for peer reviewed venues
- Bridge AI research to machine learning engineering validation pipelines
- Build train and optimize machine learning models for NGS ctDNA and digital pathology
- Create high integrity data packages for clinical governance
- Design clinical investigation and evaluation frameworks
- Design fine tuning probing and latent space analysis workflows
- Develop peer review frameworks and provide technical feedback
- Engineer alignment and post training workflows for foundation models
- Identify dataset bias and covariate shift and implement mitigation
- Lead post training parameter efficient fine tuning and evaluation
- Provide technical leadership for translational AI models
- Represent translational AI capabilities at conferences
- Support external collaborations and pharmaceutical partnerships
- Translate clinical requirements into machine learning problem statements
- Validate model outputs against multi omic benchmarks
Perks/Benefits
- 401k benefits
- Commuter benefits
- Disability insurance
- Employee referral program
- Employee testing
- Fertility care benefits
- Life insurance
- Medical/Dental/Vision insurance
Skills/Tech-stack
Captum | Cloud Computing | Covariate Shift | Covariate shift mitigation | Digital Pathology | Distributed GPU | Distributed GPU computing | Efficient Fine Tuning | Fine Tuning | GPU Computing | High Performance | High-Performance Computing | Huggingface | Latency shift mitigation | Loss Curves | MLflow | Model Evaluation | Multimodal modeling | Next-Generation Sequencing | Optimization | PEFT | Parameter efficient fine-tuning | Performance Computing | Precision-recall | Probabilistic Modeling | PyTorch | Representation Learning | Self-Supervised Learning | Self-supervised | Supervised Learning | Transformers
Education
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