Senior Machine Learning Scientist
Company: Freenome
Location: Brisbane
Posted on: July 8, 2025
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Job Description:
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. 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.
Keywords: Freenome, Fremont , Senior Machine Learning Scientist, Science, Research & Development , Brisbane, California