Staff Engineer, System Integration

Quantum-Si•San Diego, CA

5h•$175,000 - $190,000

About The Position

Quantum-Si is looking for a highly motivated and experienced Staff Engineer, System Integration to make impact on the development of our next generation protein sequencer. As part of our team, your core responsibilities will be:

Requirements

B.S. in Biomedical Engineering, Biological Engineering, Electrical Engineering, or related field. (PhD Preferred)
8+ years experience
Programming experience, such as Python, C or C++
Strong attention to detail, ability to follow complex protocols accurately and reproducibly.
Ability to analyze complex, ambiguous problems. Evaluate multiple hypotheses and test systematically.
Excellent communication skills are required, and the ability to interact well in group meetings/working environments
Self-starter with a relentless work ethic who can work independently, but who also functions well in a collaborative team environment
Demonstrated team skills: ability to maintain excellent rapport with colleagues in the face of tight development schedules
Travel: Up to 10%

Nice To Haves

Experience with:
Next generation sequencing workflows
Opto-mechanical systems, including precision alignment of optics
Experience working in start-up environments

Responsibilities

Ensure continuous operation and minimal downtime of test stands and alpha-stage instruments by performing rapid troubleshooting and system-level diagnostics.
Design and implement Python scripts and utilities to support system-level diagnostics and troubleshooting of next generation protein sequencing instruments.
Collaborating with design and development teams to implement fixes and upgrades.
Integrate hardware and control software. Develop and execute integration test plans to verify system functionality and performance.
Act as a bridge between hardware, software, and scientific teams. Communicate integration challenges and solutions clearly across disciplines.
Grasp how subsystems (optics, electronics, software, biology) interact. Predict how changes in one domain affect others.
Use structured methods to isolate issues. Comfortable with iterative debugging and hypothesis testing. This includes the ability to perform complex data analysis.
Understand the scientific principles behind the instrument’s function. Interpret experimental data to validate or refute system behavior.
Develop novel workarounds or design tweaks when standard solutions fail. Think outside the box while staying grounded in engineering principles.

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