Remote ML Scientist, Multimodal AI in Oncology

Bazeta; United States; Remote; USD 125,000 - 172,000; Full time

Benefits offered by this job

Competitive benefits package

Remote work in USA

Job summary

Natera is seeking a Senior Machine Learning Scientist to advance multimodal AI across digital pathology, genomics, transcriptomics, and cfDNA. You will design and deploy deep learning models, integrate imaging with molecular and clinical data, and build scalable workflows on cloud infrastructure.

Collaboration with pathologists, bioinformaticians, and software engineers is essential. Ideal candidates hold a PhD in a quantitative field and have hands-on PyTorch/Python experience, with a track

Qualifications

• PhD in Computer Science, Computational Biology, Biomedical Engineering, Bioinformatics, Statistics, or related quantitative discipline with ML/AI focus.
• Core experience developing ML models for biomedical applications: medical imaging, computational pathology, genomics, transcriptomics, multi-omics, molecular diagnostics.

Responsibilities

• Design, implement, and evaluate deep learning models across biomedical modalities.
• Develop multimodal AI architectures integrating imaging, molecular, and clinical data.
• Build production-quality ML workflows using cloud infrastructure (AWS).
• Collaborate with cross-functional teams to translate prototypes into validated tools.
• Analyze model outputs to generate reproducible biological and clinical insights.

Skills

PyTorch

Python

Cloud computing

Distributed training

Transformers

Education

PhD in Computer Science or related field

Tools

AWS

Job description

Natera is seeking a Senior Machine Learning Scientist to advance multimodal AI across digital pathology, genomics, transcriptomics, and cfDNA. You will design and deploy deep learning models, integrate imaging with molecular and clinical data, and build scalable workflows on cloud infrastructure.

Collaboration with pathologists, bioinformaticians, and software engineers is essential. Ideal candidates hold a PhD in a quantitative field and have hands-on PyTorch/Python experience, with a track