Senior Machine Learning Scientist

Why join Freenome?

Freenome is a high-growth biotech company developing tests to detect cancer using a standard blood draw. To do this, Freenome uses a multiomics platform that combines tumor and non-tumor signals with machine learning to find cancer in its earliest, most-treatable stages. 

Cancer is relentless. This is why Freenome is building the clinical, economic, and operational evidence to drive cancer screening and save lives. Our first screening test is for colorectal cancer (CRC) and advanced adenomas, and it’s just the beginning. 

Founded in 2014, Freenome has ~400 employees and continues to grow to match the scope of our ambitions to provide access to better screening and earlier cancer detection.  

At Freenome, we aim to impact patients by empowering everyone to prevent, detect, and treat their disease. This, together with our high-performing culture of respect and cross-collaboration, is what motivates us to make every day count.

Become a Freenomer

Do you have what it takes to be a Freenomer? A “Freenomer” is a determined, mission-driven, results-oriented employee fueled by the opportunity to change the landscape of cancer and make a positive impact on patients’ lives. Freenomers bring their diverse experience, expertise, and personal perspective to solve problems and push to achieve what’s possible, one breakthrough at a time.

About this opportunity:

At Freenome, we are seeking a Senior Machine Learning Scientist to join the Machine Learning Science team, within the Computational Science department. 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. 

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.

What you’ll do:

• 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

Must haves:

• 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

Nice to haves:

• Experience in leveraging LLMs for EHR or other RWD data in healthcare or diagnostics
• Demonstrated experience in integrating diverse data types with EHR data for multimodal analysis.
• 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 system 

Benefits and additional information:

The US target range of our base salary/hourly rate for new hires is $173,780 - $263,200. You will also be eligible to receive pre-IPO equity, cash bonuses, and a full range of medical, financial, and other benefits depending on the position offered.  Please note that individual total compensation for this position will be determined at the Company’s sole discretion and may vary based on several factors, including but not limited to, location, skill level, years and depth of relevant experience, and education. We invite you to check out our career page @ freenome.com/job-openings/ for additional company information.  

Freenome is proud to be an equal-opportunity employer, and we value diversity. Freenome does not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, veteran status, or any other status protected under federal, state, or local law.

Applicants have rights under Federal Employment Laws.  

• Family & Medical Leave Act (FMLA)
• Equal Employment Opportunity (EEO)
• Employee Polygraph Protection Act (EPPA)

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