Senior Machine Learning Scientist
$173,775–$246,750 year
Remote · United States or Brisbane, California, United States
Job Summary
Lead development of ML/DL models for cancer detection from blood samples, building on ML/DL and statistical methods to identify molecular signals. Collaborate with computational biologists, molecular biologists, and ML engineers to design and drive experiments, enabling impactful research in cancer discovery. Independently pursue cutting-edge AI research applied to biology (genomics, immunology, computational biology) and build models that generalize to new data, with emphasis on interpretability to suggest potential biological mechanisms. This role interfaces with ML engineering to ensure scalable training/iteration and requires a mindful, transparent approach to research. The position is Hybrid in Brisbane, CA (2-3 days in office) or remote, reporting to the Director, Machine Learning Science.
Required Qualifications
- PhD or equivalent research experience with an AI emphasis in Computer Science, Statistics, Mathematics, Engineering, Computational Biology, or Bioinformatics
- 3+ years of postdoc or post-PhD industry experience with impactful results in modeling
- Expertise in applied ML, deep learning and complex data modeling
- Strong understanding of ML models (GLMs, kernel methods, trees/forests, neural networks)
- Strong understanding of DL models (foundational models, LLMs)
- Experience with supervised, self-supervised, and contrastive learning
- Proficiency with Python, R, Java, C, C++, etc.
- Proficiency with ML frameworks (PyTorch, TensorFlow, Jax) and platforms (Hugging Face)
- Experience with tools like TensorBoard, MLflow, Weights & Biases
- Excellent cross-disciplinary communication and collaboration
- Passion for innovation and iterative research
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