Job description

About this opportunity: As a Senior Bioinformatics Research Engineer, you will work on Freenome’s computational platform for R&D, developing and deploying bioinformatics research software and tooling. As part of an interdisciplinary R&D team, you will work in close collaboration with computational biologists, machine learning scientists and software engineers. You will develop cutting edge solutions at the intersection of machine learning, genetic sequencing technology, biological data, and distributed systems. These contributions will drive our mission to diagnose cancer at its most actionable and early stages. The role reports to the Director of Bioinformatics Research Engineering. 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: Work at the intersection of computational biology, machine learning research, software engineering and biological data. Lead the development of Freenome’s bioinformatics research engineering framework and internal tools. Build for significant growth and scaling challenges as we transition from research to product development. Engineer robust and reproducible data pipelines that enable cutting edge liquid biopsy research. Manage and integrate data sources across the company (laboratory, bioinformatics, clinical) to enable advanced multiomic analysis. Improve the reliability and scalability of our science platform as it grows. Develop software and workflows that support a long term vision for bioinformatics research and production. Enable data driven science discoveries in biology and healthcare. Must haves: PhD in a quantitative field such as computational biology, cancer biology, statistics, bioinformatics, computer science, or B.S./M.S. and equivalent experience. 4+ years of experience with bioinformatics infrastructure, automation, and software engineering. Robust history of delivering major technical projects or analyses. Strong computational and programming skills, in Python or equivalent, including thorough experience with large scale systems and user bases. Fundamental understanding of bioinformatics, including the central dogma, molecular or cancer biology, or familiarity with regulatory processes. Experience in NGS data analysis and bioinformatic pipelines. 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 systems. Demonstrated ability to partner with laboratory and computational scientists to translate scientific roadmaps into concrete products. Ability to operate in a highly cross-functional environment where collaboration across disciplines is absolutely necessary. Nice to haves: Experience in applying statistical methods and algorithms to large-scale datasets. Experience in analyzing one or more of the following biological modalities: epigenomics, proteomics (including mass spectrometry), transcriptomics (RNA-seq). Track record of selflessly supporting and growing highly effective teams. Benefits and additional information: The US target range of our base salary rate for new hires is $161,925 - $227,325 . You will also be eligible to receive 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) California applicants please review the CCPA Notice at Collection here: California Consumer Privacy Act (CCPA) #LI-HYBRID

Requirements

Must-haves

Work at the intersection of computational biology, machine learning research, software engineering and biological data.
Lead the development of Freenome’s bioinformatics research engineering framework and internal tools.
Build for significant growth and scaling challenges as we transition from research to product development.
Engineer robust and reproducible data pipelines that enable cutting edge liquid biopsy research.
Manage and integrate data sources across the company (laboratory, bioinformatics, clinical) to enable advanced multiomic analysis.
Improve the reliability and scalability of our science platform as it grows.
Develop software and workflows that support a long term vision for bioinformatics research and production.
Enable data driven science discoveries in biology and healthcare.
PhD in a quantitative field such as computational biology, cancer biology, statistics, bioinformatics, computer science, or B.S./M.S. and equivalent experience.
4+ years of experience with bioinformatics infrastructure, automation, and software engineering.
Robust history of delivering major technical projects or analyses.
Strong computational and programming skills, in Python or equivalent, including thorough experience with large scale systems and user bases.
Fundamental understanding of bioinformatics, including the central dogma, molecular or cancer biology, or familiarity with regulatory processes.
Experience in NGS data analysis and bioinformatic pipelines.
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 systems.
Demonstrated ability to partner with laboratory and computational scientists to translate scientific roadmaps into concrete products.
Ability to operate in a highly cross-functional environment where collaboration across disciplines is absolutely necessary.
Applicants have rights under Federal Employment Laws.
Family & Medical Leave Act (FMLA)
Equal Employment Opportunity (EEO)

Nice-to-haves

Experience in applying statistical methods and algorithms to large-scale datasets.
Experience in analyzing one or more of the following biological modalities: epigenomics, proteomics (including mass spectrometry), transcriptomics (RNA-seq).
Track record of selflessly supporting and growing highly effective teams.

Application prep

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Keywords to mirror

machine learningpythondockergcpazureaws

Platform: greenhouse
Effort: quick

Benefits

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Vision

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