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Freenome

Blood-based multiomics cancer detection tests

Senior Staff Software Engineer

Platform EngineeringConfirmed live in the last 24 hours
Full-timeRemote in USA

About the Job

Requirements

  • 12+ years of relevant software engineering experience or equivalent, preferably in platform teams, delivering complex systems from design to production.
  • 3+ years guiding complex initiatives end-to-end across teams, aligning stakeholders, communicating tradeoffs clearly, and enabling delivery without formal authority.
  • 3+ years building and operating production platforms using Infrastructure as Code on a public cloud, preferably Azure or GCP.
  • Proficiency in Python and at least one other high-level programming language.
  • Deep knowledge of Linux internals, networking, and virtualization, with hands-on troubleshooting and performance tuning at system level.
  • Solid Kubernetes expertise, with experience owning one or more advanced capabilities such as controllers, operators and CRDs, admission control, scheduling, autoscaling, service mesh, or multi-cluster networking.
  • Sound judgment in distributed systems and platform design, including governance, capacity, reliability, cost, data processing, and storage.
  • Software architecture leadership, including shipping clean code, writing clear design documents and ADRs, and guiding constructive reviews and collaborative technical decisions.
  • Track record of helping engineers or domain experts grow and making teams more capable and independent.
  • Success partnering with one or more specialist teams, such as data science, AI/ML, computational biology, or related fields, to improve their workflows.
  • Hands-on AI-assisted development and a record of building reusable tools or workflow automation.

Responsibilities

  • Shape Platform’s technical vision and roadmap, working with engineering and R&D leaders to align platform priorities with company goals.
  • Treat Platform and Data as products by building trust with leads and subject-matter experts from domain teams and translating shared needs into reusable platform solutions.
  • Design and ship scalable platform systems, evolving the architecture through reviews, rapid prototypes, and pragmatic technology choices.
  • Drive business-critical initiatives by resolving tradeoffs, sequencing work into incremental deliverables, and delegating to scale execution.
  • Support platform users to unblock critical work, troubleshoot complex system issues, and turn recurring issues into lasting reliability and capacity improvements.
  • Champion AI adoption across Freenome, pairing with domain experts and tailoring guidance and tools to varied technical backgrounds.
  • Use AI for platform enhancements and build platforms for AI that empower users to create and deploy secure, cost-effective agentic workflows and large language model-powered applications.
  • Increase visibility of cloud costs and recommend and drive initiatives to reduce waste while protecting performance, reliability, and scientific productivity.
  • Grow other engineers through pairing, design review, delegation, and feedback, while modeling company values and reinforcing a high-performing culture.

Desired Qualifications

  • Experience, familiarity, or genuine interest in life-sciences software, NGS pipelines, and biological data.
  • Experience, familiarity, or genuine interest in machine learning operations, model development, and deep learning.
  • Experience, familiarity, or genuine interest in scientific Python frameworks and the data-science technology stack.
  • Experience, familiarity, or genuine interest in workflow orchestration and distributed compute frameworks on Kubernetes.
  • Experience, familiarity, or genuine interest in cloud migrations, multi-cloud, or multi-region operations.
  • Experience, familiarity, or genuine interest in columnar processing, open lakehouse technologies, and modern table formats such as Apache Iceberg.
  • Experience, familiarity, or genuine interest in FinOps practices, workload cost attribution, and measurable cloud savings.

About the Company

Freenome

Blood-based multiomics cancer detection tests

Freenome develops non-invasive blood tests for early cancer detection using a multiomics approach that analyzes genomic and proteomic data from blood. The test works by measuring biomarkers in a blood sample and applying algorithms to estimate cancer risk or presence, with results shared with healthcare providers and researchers. It differentiates itself by combining multiple data types and pursuing large clinical trials and collaborations to validate the tests. The goal is to make early, non-invasive cancer screening a routine part of healthcare, expanding nationwide efforts, especially for colorectal cancer, to improve detection and patient outcomes.

Company size
201-500
Company stage
IPO
Headquarters
Brisbane, CA
Founded
2014

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