Live opening · Posted 4 days ago

Staff Systems Integration Engineer

Cellanome · San Diego, CA
Greenhouse
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At a glance

The key details from the original listing.

Posted 4 days ago
CompanyCellanome
LocationSan Diego, CA
SourceGreenhouse
Listed4 days ago

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About the role

Description supplied by the original job listing.

We’re a well-funded start-up. You’ll get a chance to wear many hats, be a part of a growing team, and have the potential for exciting financial and career growth.
Here’s what sets us apart. We’ve set our sights on some of the biggest challenges facing biology today. We’re amassing a world class team of engineers, scientists, team builders and problem solvers to tackle these challenges heads-on. We’re passionate about developing the next generation technologies that will unravel the complexities of biology.
This is a unique opportunity to build, be part of an exciting start-up and be surrounded by good humans who are super capable, humble and down-to- earth.
The Staff Systems Integration Engineer is a core member of the Product Development team and will work in close collaboration with other Engineers and Scientists to automate and troubleshoot existing protocols onto a prototype instrument developed in-house, and to create new ones. We are looking for someone that has the right experience to drive the integration of biological protocols with novel hardware and can hit the ground running. We encourage the use of AI coding assistants and automation tooling to accelerate optimization and troubleshooting. This role reports to the SVP of Product Development.
Essential Duties include:
Designing experiments to test prototype hardware.
Troubleshooting issues arising at the hardware, software, consumables, and workflow interface.
Transferring existing molecular biology and cell biology protocols to a first of its kind instrumentation platform.
Working in close collaboration with the Engineering and Scientific teams to troubleshoot protocols and software/hardware/assay issues.
Gathering requirements for the Engineering and Service teams.
Using AI coding assistants to write and maintain automation, data-analysis, and instrument-control code.
Building AI-assisted tooling (scripted LLM workflows, agents, and internal copilots) that accelerates optimization, experiment design, and failure-mode triage.
Applying AI/ML-assisted analysis to instrument and assay data to detect drift, classify failure modes, and shorten troubleshooting cycles.
Ability to lift up to 40 lbs for approximately 10% of typical working day.
Ability to travel up to 20% of working time away from work location, may include overnight/weekend and international travel at times.
Minimum Qualifications:
Typically requires a minimum of 8 years of related experience with a bachelor’s degree; or 6 years and a Master’s degree; or a PhD with 3 years of experience.
Degree in relevant Engineering discipline or Biologic/Physical Sciences.

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