C

Cellanome

Automated platform for live single-cell assays

Staff Systems Integration Engineer

Biomedical Engineering & Medical DevicesConfirmed live in the last 24 hours
Full-timeSan Diego, CA, USAIn-person

About the Job

Requirements

  • Typically requires at least 8 years of related experience with a bachelor’s degree, 6 years with a master’s degree, or 3 years with a PhD.
  • A degree in a relevant Engineering discipline or Biological or Physical Sciences.
  • Previous experience as part of commercial development teams.
  • Experience in instrumentation development and troubleshooting low-level hardware issues.
  • Familiarity and basic competence with standard wet-lab molecular biology protocols and sample-preparation protocols.
  • Solid data analysis and visualization skills.
  • Working proficiency in Python or an equivalent language for scripting, data analysis, and automation.
  • Hands-on use of AI tools, such as large language model coding assistants or agentic workflows, to accelerate engineering or laboratory work.
  • Ability to lift up to 40 pounds for approximately 10% of a typical working day.
  • Ability to travel up to 20% of working time away from the work location, potentially including overnight, weekend, and international travel.
  • Ability to perform the essential duties with or without reasonable accommodations.

Responsibilities

  • Design experiments to test prototype hardware.
  • Troubleshoot issues at the hardware, software, consumables, and workflow interface.
  • Transfer existing molecular biology and cell biology protocols to a first-of-its-kind instrumentation platform.
  • Collaborate with Engineering and Scientific teams to troubleshoot protocols and software, hardware, and assay issues.
  • Gather requirements for the Engineering and Service teams.
  • Use AI coding assistants to write and maintain automation, data-analysis, and instrument-control code.
  • Build AI-assisted tooling, including scripted large language model workflows, agents, and internal copilots, to accelerate optimization, experiment design, and failure-mode triage.
  • Apply AI- and machine-learning-assisted analysis to instrument and assay data to detect drift, classify failure modes, and shorten troubleshooting cycles.

Desired Qualifications

  • Experience with Python and C#.
  • Experience building AI-assisted tooling, such as prompt engineering, retrieval over technical documentation, or agentic scripting, for engineering or laboratory workflows.
  • Experience integrating AI or machine-learning models into production labs or manufacturing workflows.
  • Experience working with biological workflows.

About the Company

Cellanome

Automated platform for live single-cell assays

Cellanome builds an automated platform for live-cell analysis to study single-cell behaviors, interactions, and functions under different conditions at scale. Researchers run iterative live-cell phenotypic and functional assays, observing how individual cells respond to stimuli over time. The platform integrates into existing cell biology workflows as a software-and-instrument solution offered by subscription or licensing, enabling high-throughput data collection across many cells. Compared with traditional bulk methods, it focuses on single-cell detail, scalable data, and easy workflow integration to accelerate discovery in life sciences and medicine.

Company size
51-200
Company stage
Series C
Total funding
$276.9M
Headquarters
Foster City, CA
Founded
2020

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