Senior Machine Learning Scientist, Freenome

• The ideal candidate has a strong knowledge of artificial intelligence (AI), including machine learning (ML) fundamentals and extensive experience with deep learning (DL) and large language models (LLMs), a track record of successfully using these methods to answer complex research questions, and the ability to thrive in a highly cross-functional environment
• PhD or equivalent research experience with an AI/DL emphasis and in a relevant, quantitative field such as Computer Science, Statistics, Mathematics, Computational Biology with a strong track record in natural language processing
• 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 multimodal data modeling
• Extensive experience in working with DL models, LLMs, and multimodal foundation models
• Extensive experience with training paradigms like supervised learning, self-supervised learning, and contrastive learning
• Practical and theoretical understanding of fundamental ML models like generalized linear models, kernel machines, decision trees and forests, neural networks
• Solid grasp of NLP techniques, including but not limited to named entity recognition (NER), text summarization, and question answering
• Proficiency in a general-purpose programming language: Python (preferred), Java, C, C++, etc
• Proficiency in one or more ML frameworks such as Pytorch, Tensorflow, and Jax; LLM specific frameworks like LangChain; 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

Desirable

• At Freenome, we are seeking a Senior Machine Learning Scientist to join the Machine Learning Science team, within the Computational Science department
• They will primarily be responsible for the development of algorithms and pipelines to analyze vast amounts of electronic health records (EHR) and other real world data (RWD) to support Freenome’s early blood-based detection tests for cancer
• Their expertise in AI, natural language processing, and multimodal data analysis will be crucial in extracting insights from complex datasets, driving the development of next-generation diagnostic tests
• They will collaborate with a multidisciplinary team of scientists, informaticians and ML engineers to design and drive research experiments, and to help Freenome achieve its mission of reducing cancer mortality via accessible early detection
• This role can be a hybrid role based in our Brisbane, California headquarters (2-3 days per week in office), or remote
• Independently pursue cutting edge research using advanced AI algorithms and LLMs to analyze EHR data, extracting relevant information for cancer detection
• Stay abreast of the latest developments in LLMs for natural language processing (NLP) and apply these models directly or after fine-tuning for clinical data analysis at Freenome
• Design and develop AI pipelines, working closely with ML engineers, to increase efficiency of biomedical and clinical data extraction, processing, and interpretation
• Collaborate with clinical data scientists and informaticians to understand data requirements and ensure the accuracy and relevance of AI-generated insights
• Collaborate with machine learning scientists to integrate EHR data with non-EHR d data sources, such as genomics or proteomics data, building robust multimodal models for cancer detection
• Lead the development and optimization of algorithms and models that leverage diverse data types, ensuring high accuracy and reliability and predictions
• Take a mindful, transparent, and humane approach to your work