Senior Machine Learning Scientist

Summary

Join Freenome, a high-growth biotech company, as a Senior Machine Learning Scientist to contribute to the development of blood-based cancer detection tests. You will build and refine machine learning models, collaborate with cross-functional teams, and conduct cutting-edge research in AI applied to biological problems. This hybrid or remote role reports to the Director, Machine Learning Science and offers the opportunity to significantly impact cancer research and patient care. The ideal candidate possesses extensive experience in deep learning, a strong publication record, and proficiency in various programming languages and ML frameworks. Freenome provides a competitive salary, pre-IPO equity, cash bonuses, and a comprehensive benefits package.

Requirements

• PhD or equivalent research experience with an AI/DL emphasis and in a relevant, quantitative field such as Computer Science, Statistics, Mathematics, Engineering, Computational Biology, or Bioinformatics
• 3+ years of postdoc or post-PhD industry experience achieving impactful results using relevant modeling techniques
• Expertise, demonstrated by research publications or industry achievements, in applied machine learning, deep learning and complex data modeling
• Practical and theoretical understanding of fundamental ML models like generalized linear models, kernel machines, decision trees and forests, neural networks, boosting and model aggregation, Bayesian inference and model selection, and variational inference
• Practical and theoretical understanding of DL models like large language models or other foundation models
• Extensive experience with training paradigms like supervised learning, self-supervised learning, and contrastive learning
• Proficient in current state of the art in ML/DL approaches in different domains, with an ability to envision their applications in biological data
• Proficiency in a general-purpose programming language: Python, R, Java, C, C++, etc
• Proficiency in one or more ML frameworks such as; Pytorch, Tensorflow and Jax; and ML platforms like Hugging Face
• Experience in ML analysis and developer tools like TensorBoard, MLflow or Weights & Biases
• Excellent ability to communicate across disciplines, work collaboratively, and make progress in smaller steps via experimental iterations
• A passion for innovation and demonstrated initiative in tackling new areas of research

Responsibilities

• Independently pursue cutting edge research in AI applied to biological problems (including cancer research, genomics, computational biology, immunology, etc.)
• Build new models or fine-tune existing models to identify biological changes resulting from disease
• Build models that achieve high accuracy and that generalize robustly to new data
• Apply contemporary interpretability techniques to provide a deeper understanding of the underlying signal identified by the model, ideally suggesting potential biological mechanisms
• Work closely with ML Engineering partners to ensure that Freenome’s computational infrastructure supports optimal model training and iteration
• Take a mindful, transparent, and humane approach to your work

Preferred Qualifications

• Deep domain-specific experience in computational biology, genomics, proteomics or a related field
• Experience in building DL models for genomic data, with knowledge of state-of-the-art DNA foundation models
• Experience in NGS data analysis and bioinformatic pipelines
• Experience with containerized cloud computing environments such as Docker in GCP, Azure, or AWS
• Experience in a production software engineering environment, including the use of automated regression testing, version control, and deployment systems

Benefits

• Pre-IPO equity
• Cash bonuses
• A full range of medical, financial, and other benefits
• Family & Medical Leave Act (FMLA)
• Equal Employment Opportunity (EEO)
• Employee Polygraph Protection Act (EPPA)