Key Responsibilities
Develop, maintain, debug, and improve Python-based instrument-control software.
Quickly understand and take ownership of portions of a large existing codebase.
Diagnose failures involving interactions between software and multiple hardware
subsystems.
Debug complex integration issues across robotics, motion control, sensors,
imaging, microfluidics, and custom electronics.
Investigate intermittent and difficult-to-reproduce instrument failures.
Improve stability, reliability, observability, and fault handling throughout the
instrument-control platform.
Integrate Python applications with hardware devices and custom firmware
interfaces.
Work with real-time or near-real-time telemetry generated by multiple instrument
components.
Analyze logs, telemetry, device state, and system behavior to identify root causes.
Develop robust error recovery and fault-management mechanisms.
Collaborate directly with firmware, electrical, mechanical, systems, scientific, and
software engineers.
Support instrument integration, testing, and troubleshooting on physical hardware.
Improve documentation and engineering knowledge transfer within the instrument-
control codebase.
Contribute to architectural improvements as the platform matures.
Required Skills
7+ years of software engineering experience, with significant hands-on Python
development.
Advanced proficiency with Python in production systems.
Strong Linux experience, including command-line debugging, processes,
permissions, networking basics, logs, and device interaction.
Demonstrated experience integrating software with physical hardware or embedded
systems.
Experience controlling or coordinating multiple hardware components
simultaneously.
Strong debugging skills across complex distributed or hardware-integrated systems.
Experience consuming, processing, or troubleshooting real-time/streaming
telemetry.
Understanding of asynchronoconcurrent programming and event-driven
systems.
Experience interfacing Python applications with firmware, embedded controllers,
device APIs, serial interfaces, network-connected devices, or similar systems.
Ability to understand unfamiliar, complex codebases quickly.
Strong software engineering fundamentals, including testing, version control, code
review, and maintainable architecture.
Excellent communication skills and comfort working across software and hardware
engineering disciplines.
Strongly Preferred
Scientific instrumentation, laboratory automation, robotics, medical devices,
semiconductor equipment, industrial automation, motion-control systems, machine
vision/imaging systems, microfluidics, or hardware-in-the-loop systems.
Experience with motion controllers, motors, stages, actuators, or robotic positioning
systems.
Experience with cameras, sensors, or imaging pipelines.
Experience with serial communication, USB, Ethernet-connected devices, CAN,
Modbus, or similar hardware protocols.
Experience with custom firmware interfaces, state machines, and device
orchestration.
Experience with hardware-in-the-loop testing, simulation, or digital-twin
environments.
Experience with telemetry, observability, logging, and failure analysis.
Experience with AWS or cloud-connected instrumentation.
