Senior Machine Learning Scientist
South San Francisco, CA

Job Description

About the Role

As a Machine Learning Scientist at Freenome, you will be an integral part of our R&D team, working in close collaboration with computational biologists and software engineers to develop and deploy the statistical models driving our mission of early detection and intervention in human disease.

Responsibilities

* Collaborate within an interdisciplinary technical team to develop your science into Freenome's product
* Participate in cutting edge research in statistical modeling and inference of biological problems (including cancer research, genomics, computational biology/bioinformatics, immunology, therapeutics, and more)
* Build and immediately apply core analysis technologies to solve patients' and doctors' healthcare needs
* Discover science that generalizes in support of a long term research program in data driven biology
* Interface with product teams to identify potential new problem areas in need of an ML solution
* Take a mindful, transparent, and humane approach to your work

What We're Looking For

* PhD (or equivalent research experience) in computer science (AI or ML emphasis), statistics, applied math, or a related field
* Expertise, demonstrated by research publications or industrial experience, in applied machine learning, data mining, pattern recognition, or AI
* Experience building statistical models from a variety of input data types: text, images, audio, structured data, time series events, etc
* Proficiency in a general-purpose programming language: Python, Java, C, C++, etc
* Familiarity working in a Linux server-based environment
* Strong knowledge of mathematical fundamentals: statistics, probability theory, linear algebra
* Practical and theoretical understanding of fundamental models and algorithms in supervised and unsupervised learning: generalized linear models, kernel machines, decision trees, neural networks; boosting and model aggregation; clustering and mixture modeling; EM, variational inference, and local/global optimization; dimensionality reduction and manifold learning
* Ability to clearly communicate across disciplines and work collaboratively towards next steps in experimental iterations

Nice to Haves

* Domain-specific experience in computational biology, genomics or a related field
* Experience in scientific parallel computing
* Experience in high-performance computing, including SIMD or GPU performance optimization
* Experience in a production software engineering environment, including use of automated regression testing, version control, and deployment systems

About Freenome

Freenome is on a mission to empower everyone with the tools they need to detect, treat, and ultimately prevent diseases.

By applying machine learning techniques to high-quality multi-omics datasets covering various disease types, Freenome is developing blood tests to detect early-stage cancer and make treatments more effective. The company has raised $78 million from investors such as Andreessen Horowitz, Google Ventures, Polaris Partners, and Founders Fund.

Our Science

Freenome is building technology to gain an understanding of the body through several analytes derived from blood. These signals include cell-free DNA, methylation of cell-free DNA, cell-free RNA, circulating proteins, and immune profiling derived from thousands of prospective samples. By developing novel statistical learning methods and applying them to integrate various -omics datasets, Freenome is a leader in modeling specific biological mechanisms to capture disease dependent signatures such as gene expression, immune response, tumor burden, the tissue of origin, and 3D chromatin structure.

By building comprehensive discovery datasets and modeling critical biological systems, Freenome is learning what biological changes are present within the blood between a variety of different disease states including cancer, autoimmune disorders, infections, drug response, and aging. With the combination of Freenome's datasets, cross-functional technical expertise, and mission to uncover the biological truth, we seek to positively change the lives of millions through the early detection and early treatment of disease.

Our Culture

Freenomers are technical but creative, visionary yet grounded, empathetic and passionate. We build teams around divergent expertise, which allows us to solve problems and uncover opportunities in unique ways. Freenomers are some of the most talented experts in their fields. Together we advance healthcare one breakthrough at a time.

We value empathy, integrity and trust in one another. That means embracing other's perspectives, those of our coworkers, and those of the patients and communities we serve. It means knowing when to push and when to be quiet and listen. At Freenome we give each other the benefit of the doubt in the belief that we're all working as a team toward the same goals. We conduct ourselves with integrity, empowering others to grow in a collaborative environment.

Freenome explicitly prohibits any form of workplace harassment based on race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status.

What does a successful person look like at Freenome?

Those who thrive at Freenome prioritize, manage, and execute their own goals in alignment with those of the company. They embrace our values of empathy, integrity, and trust, and hold themselves and their team accountable. They crave collaboration with brilliant minds from unfamiliar fields of study and believe that hiring and mentorship are fundamental to our success. Above all, they welcome and provide constructive feedback and criticism, trusting in the good intentions of others, and feel secure in the knowledge that embracing mistakes is the best way to learn and move on. For those who crave challenges, understudied problems, and the chance to see their work impact the lives of millions of people affected by cancer every day, Freenome is the place to be.