This position is open to remote work within the US or onsite work at our headquarters in South San Francisco. Our working hours are 9-5pm PT.

Why join Freenome?

Freenome is a high-growth biotech company on a mission since 2014 to create tools that empower everyone to prevent, detect, and treat their disease. 

To achieve this mission, Freenome is developing next-generation blood tests to detect cancer in its earliest, most treatable stages using our multiomics platform and machine learning techniques. Our first blood test will detect early-stage colorectal cancer and advanced adenomas.

To fight the war on cancer, Freenome has raised more than $1.1B from leading investors including a16z, GV (formerly Google Ventures), T. Rowe Price, BainCapital, Perceptive Advisors, RA Capital Management, Roche, Kaiser Permanente Ventures, and the American Cancer Society’s BrightEdge Ventures.

Are you ready for the fight? A ‘Freenomer’ is a mission-driven employee who is fueled by the opportunity to make a positive impact on patients’ lives, who thrive in a culture of respect and cross collaboration, and whose work makes a significant impact on the company and their career. Freenomers are determined, patient-centric,  and outcomes-driven. We build teams around divergent expertise, allowing us to solve problems and ascertain opportunities in unique ways. We are dedicated to advancing healthcare, one breakthrough at a time.

About this opportunity:

As the Director of Machine Learning (ML) Science at Freenome, you will provide technical vision and scientific leadership for a group of talented ML scientists. You will also partner closely with Freenome’s ML Research Engineering group, which implements and maintains Freenome’s ML model development infrastructure. 

You and your team will leverage a deep understanding of ML methods, theory and application, and you will work in partnership with computational biologists to develop robust and performant classifiers for early cancer detection, based on multiomics molecular signals in the blood. 

You will provide inspiration and technical guidance to team members, helping them to grow and develop, and empowering them to do their best work. 

Finally, you will be a key member of Freenome’s scientific and engineering leadership teams, contributing to decision making and prioritization.

What you’ll do: 

• Lead a team that develops robust and performant classifiers for early cancer detection, based on multiomics molecular signals in the blood. 
• Be an expert in current statistical modeling and ML techniques — one who is able to rapidly evaluate and select methodologies that are appropriate for Freenome’s data types, and to develop new approaches when required.
• Serve as a key thought leader on engineering and scientific leadership teams. 
• Be capable of guiding the scientific work of your team and also digging into the code and data directly.
• Collaborate with computational biologists to better understand the nature of the underlying assays, molecular signals and biological systems, in order to maximize the predictive value of our training data.
• Work closely with ML research engineers to help them optimize infrastructure and better support the evaluation and development of new ML architectures.
• Nurture and grow a high-functioning ML Science team, by mentoring existing staff and recruiting new staff with skill sets and development goals aligned with Freenome’s mission.
• Possess an ability to explain complex modeling methodologies to staff in other disciplines, in order to increase their understanding of Freenome’s products and to identify new opportunities for application of ML techniques.
• Create opportunities for team members to undertake independent work and shape their own professional directions.
• Partner with other engineering and scientific leadership at Freenome to develop roadmaps and strategies.
• Inspire a culture of innovation, translating discoveries into high-impact R&D pipelines and clinical applications.
• Exemplify Freenome’s commitment to “servant leadership” by maximizing the full team’s potential for impactful contribution. 

Must haves: 

• PhD in computer science, statistics, mathematics or other relevant scientific discipline. Alternatively, directly relevant professional experience and documented scientific achievements equivalent to a PhD in these disciplines. 
• 7+ years post-PhD (or post-PhD-equivalent) experience with statistical and ML model development. 
• Expertise with large-scale ML model development frameworks. 
• Outstanding command of modern ML model development software engineering and data architecture practices, including several of the following: 
  • Distributed high-performance computing, including workflow orchestration systems.
  • Semantic modeling and graph database techniques. 
  • Source code management (e.g., Git).
  • Containerization or other mechanisms for compute environment management.
  • One or more common ML model development frameworks (e.g., PyTorch, TensorFlow, or scikit-learn).
• 3+ years leading or managing scientific and software engineering staff.
• Track record of selflessly supporting highly effective cross-functional teams, and of collaborating closely with subject matter experts in other disciplines.

Nice to haves: 

• Experience developing ML models in Python.
• Industry experience working in a diagnostics, pharmaceutical, or other biotechnology environment.
• Experience applying ML techniques to high-dimensional molecular biology data types. 
• Experience with cloud-based high-performance computing.

Benefits and additional information:

The US target range of our base salary for new hires is $225,250 - $345,000. You will also be eligible to receive pre-IPO equity, cash bonuses, and a full range of medical, financial, and other benefits dependent 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 @ https://careers.freenome.com/ 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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