# Staff Machine Learning Scientist

**Company**: Freenome
**Location**: Brisbane, California
**Work arrangement**: hybrid
**Experience**: staff
**Job type**: full-time
**Salary**: $199,675 - $283,500
**Category**: IT
**Industry**: Healthcare

**Apply**: https://job-boards.greenhouse.io/freenome/jobs/8627491002?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_e4463086-804

## Description

We are seeking a Staff Machine Learning Scientist to join our Machine Learning Science team within the Computational Science department. As a Staff Machine Learning Scientist, you will play a key role in developing algorithms for early, blood-based detection tests for cancer. You will build on a foundation of machine learning and deep learning skills to develop models for identifying molecular signals from blood.

Responsibilities:

- Independently pursue cutting-edge research in AI applied to biological problems, including cancer research, genomics, and computational biology.

- Build new models or fine-tune existing models to identify biological changes resulting from disease.

- Develop models that achieve high accuracy and generalise robustly to new data.

- Apply contemporary interpretability techniques to provide a deeper understanding of the underlying signal identified by the model.

- Collaborate with ML Engineering partners to ensure that our computational infrastructure supports optimal model training and iteration.

- Work closely with cross-functional teams, including computational biologists, molecular biologists, and ML engineers.

Requirements:

- PhD or equivalent research experience with an AI emphasis in a relevant, quantitative field.

- 6+ years of postdoc or post-PhD industry experience achieving impactful results using relevant modeling techniques.

- Expertise in driving independent research in applied machine learning, deep learning, and complex data modeling.

- Practical and theoretical understanding of fundamental ML models, including generalised linear models, kernel machines, decision trees and forests, neural networks, boosting, and model aggregation.

- Practical and theoretical understanding of DL models, including large language models.

- Extensive experience with training paradigms like supervised learning, self-supervised learning, and contrastive learning.

- Proficient in a general-purpose programming language, such as Python, R, Java, C, or C++.

- Proficient in one or more ML frameworks, such as PyTorch, TensorFlow, or JAX.

- Experience with ML analysis and developer tools like TensorBoard, MLflow, or Weights & Biases.

- Excellent ability to communicate across disciplines and work collaboratively.

Nice to Have:

- Deep domain-specific experience in computational biology, genomics, proteomics, or a related field.

- Experience in building DL models for genomic data.

- Experience in NGS data analysis and bioinformatic pipelines.

- Experience with containerised cloud computing environments.

Benefits:

- The US target range of our base salary for new hires is $199,675 - $283,500.

- You will also be eligible to receive equity, cash bonuses, and a full range of medical, financial, and other benefits.

## Skills

### Required
- machine learning
- deep learning
- Python
- PyTorch
- TensorFlow
- JAX
- ML frameworks
- data modeling
- computational biology

### Nice to have
- genomics
- proteomics
- NGS data analysis
- bioinformatic pipelines
- containerised cloud computing environments

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Source: [Apply at job-boards.greenhouse.io](https://job-boards.greenhouse.io/freenome/jobs/8627491002?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)