Senior Bioinformatics Research Engineer (Machine Learning)

Location: Brisbane, California, United States. Hybrid attendance requires 2–3 days per week in the headquarters office; a remote work option is also available.

Salary: $161,925–$227,325 USD annual base salary, plus equity, cash bonuses, and medical, financial, and other benefits.

Company

hirify.global develops computational and biological technologies aimed at diagnosing cancer at actionable and early stages.

What you will do

• Develop and deploy bioinformatics research software, tooling, workflows, and an internal research engineering framework.
• Build robust, reproducible data pipelines supporting liquid biopsy research.
• Integrate laboratory, bioinformatics, and clinical data for advanced multiomic analysis.
• Improve the reliability, scalability, and production readiness of the science platform.
• Collaborate with computational biologists, machine learning scientists, software engineers, laboratory scientists, and clinical teams.
• Translate scientific roadmaps into concrete software products and enable data-driven discoveries in biology and healthcare.

Requirements

• PhD in computational biology, cancer biology, statistics, bioinformatics, computer science, or another quantitative field; alternatively, a bachelor’s or master’s degree with equivalent experience.
• 4+ years of experience in bioinformatics infrastructure, automation, and software engineering.
• Strong programming skills in Python or an equivalent language, including experience with large-scale systems and user bases.
• Understanding of bioinformatics, molecular or cancer biology, the central dogma, or regulatory processes, plus experience with NGS data analysis and bioinformatics pipelines.
• Experience with containerized cloud computing environments such as Docker on GCP, Azure, or AWS.
• Production software engineering experience with automated regression testing, version control, deployment systems, and cross-functional collaboration.

Nice to have

• Experience applying statistical methods and algorithms to large-scale datasets.
• Experience with epigenomics, proteomics, mass spectrometry, or transcriptomics including RNA-seq.
• Experience supporting and developing highly effective teams.

Culture & Benefits

• Interdisciplinary collaboration across biology, machine learning, software engineering, laboratory, and clinical functions.
• Hybrid work with 2–3 office days per week in Brisbane, California, or a remote work option.
• Equity and cash bonus eligibility.
• Medical, financial, and other benefits.
• Equal-opportunity workplace focused on diversity and inclusion.