Machine Learning Scientist - Remote

About the Company

Freenome is a pioneering biotechnology company dedicated to transforming cancer detection and treatment through innovative blood-based diagnostic solutions. Leveraging cutting-edge artificial intelligence, machine learning, and genomics, Freenome aims to revolutionize early cancer detection, enabling timely intervention and improved patient outcomes. The organization fosters a collaborative and inclusive environment, emphasizing scientific excellence, technological innovation, and a commitment to making a meaningful impact in healthcare. With a focus on research-driven approaches, Freenome combines expertise across computational biology, molecular biology, and data science to develop scalable, non-invasive diagnostic tools that can detect cancer at its earliest stages.

About the Role

We are seeking a highly skilled Staff Machine Learning Scientist to join our Machine Learning Science team within the Computational Science department. The ideal candidate will possess a deep understanding of artificial intelligence, particularly in machine learning and deep learning methodologies, with extensive experience applying these techniques to complex biological and medical research questions. This role involves developing sophisticated algorithms for early detection of cancer through blood-based tests, focusing on identifying molecular signals from blood samples. The successful candidate will collaborate closely with computational biologists, molecular biologists, and ML engineers to design experiments, refine models, and drive innovative research initiatives. This position offers flexibility with a hybrid work model based in Brisbane, California, or remote, and reports to the Director of Machine Learning Science.

Qualifications

• PhD or equivalent research experience in a relevant, quantitative field such as Computer Science, Statistics, Mathematics, Engineering, Computational Biology, or Bioinformatics.
• Minimum of 6+ years postdoctoral or industry experience in applied machine learning, deep learning, and complex data modeling.
• Proven track record of impactful research publications or industry achievements demonstrating expertise in AI and ML techniques.
• Strong understanding of fundamental ML models including generalized linear models, kernel methods, decision trees, neural networks, boosting, and model aggregation.
• Extensive experience with deep learning models such as large language models and foundation models.
• Hands-on experience with training paradigms like supervised, self-supervised, and contrastive learning.
• Proficiency in programming languages such as Python, R, Java, C, or C++.
• Experience with ML frameworks like PyTorch, TensorFlow, Jax, and platforms such as Hugging Face.
• Familiarity with ML analysis and developer tools like TensorBoard, MLflow, or Weights & Biases.
• Excellent communication skills with the ability to collaborate across disciplines, including software engineering and biological sciences.
• A demonstrated passion for innovation and a proactive approach to exploring new research areas.

Responsibilities

• Independently conduct cutting-edge research applying AI to biological problems, including cancer genomics, immunology, and computational biology.
• Develop new models or fine-tune existing models to detect biological changes associated with disease states.
• Create models that deliver high accuracy and demonstrate robustness and generalizability across diverse datasets.
• Apply interpretability techniques to elucidate underlying biological signals, potentially uncovering biological mechanisms.
• Collaborate with ML engineering teams to ensure computational infrastructure supports efficient model training, validation, and deployment.
• Drive experimental design, data analysis, and model iteration to optimize performance and insights.
• Contribute to scientific publications, presentations, and knowledge sharing within the organization and the broader research community.
• Maintain a transparent, ethical, and humane approach to research and development activities.

Benefits

• Competitive salary range, with a target base salary of $199,675 - $283,500 for new hires in the US.
• Eligibility for equity, cash bonuses, and comprehensive medical, dental, and vision benefits.
• Financial and wellness benefits tailored to support work-life balance and professional growth.
• Opportunities for continuous learning, conference attendance, and participation in cutting-edge research initiatives.
• Flexible work arrangements, including hybrid or remote options.