Sr. Embedded Firmware Engineer

Socket.dev; San Francisco (CA); On-site; USD 150,000 - 190,000; Full time

Job summary

Ironsite is seeking a Senior Embedded Firmware Engineer to own the firmware for our wearable hardware. You will build and optimize the camera pipeline, sensor stack, and OTA provisioning to ensure robust performance in harsh jobsite environments.

You will collaborate with hardware, manufacturing, and cloud teams to bring devices from silicon bring-up to mass production, addressing battery life, image quality, and thermal constraints for reliable day-long operation.

Qualifications

• Proven experience in firmware for wearable hardware.
• Strong C/C++ skills and real-time systems knowledge.
• Experience with STM32 or Nordic platforms and Zephyr RTOS.

Responsibilities

• Own firmware for wearable hardware and camera pipeline end-to-end.
• Develop drivers for camera, sensors, wireless, and IMU.
• Optimize for 8–12 hour wearable operation with memory and power constraints.
• Collaborate with hardware, manufacturing, and cloud teams across lifecycle.

Skills

Embedded firmware development

C/C++

Embedded systems

RTOS (Zephyr)

Camera pipeline

Sensor integration

On-device ML inference

Power/thermal optimization

Education

Bachelor's degree in Electrical Engineering or Computer Science

Tools

STM32

Nordic

Zephyr RTOS

Camera drivers

Job description

About Ironsite

Ironsite is building the intelligence layer for the physical world. We design our own wearable hardware, deploy it alongside craft workers, and transform a shift's footage into a next-morning report.

Our internal team and purpose-built models label the data overnight and deliver actionable insights to superintendents by 5 AM.

We are accelerating the speed, efficiency, and predictability of construction, especially for complex, mission-critical infrastructure projects, including data centers, LNG facilities, sports stadiums, hospitals, and other large-scale developments, by training AI models on egocentric construction footage and labor productivity data.

We are built with a pro-worker philosophy at our core: we believe technology should empower the workforce, not replace it.

We're working to give craft workers and project leaders better visibility into what's happening on-site, while creating a system where the reality of construction and the chaos of each day is finally available to the people running the project.

Ironsite is deployed across several of the largest active construction projects in the country. To date, we've captured more than 100,000 hours of construction footage across seven states, now process thousands of hours of site activity every day, and maintain a worker opt-out rate below two percent.

This is enabled by a workforce-first architecture that anonymizes devices, captures no audio, and never releases raw video.

Ironsite is backed by leading investors (8VC, South Park Commons, Saga Ventures) and prominent operators across technology and construction, including Eric Schmidt, Jeff Dean, Jeff Rothschild, Mark Leslie, Scott Wu, Eric Glyman, Karim Atiyeh, Russell Kaplan, and others, alongside over a dozen construction industry operators who have joined us as partners in building this.

Longer term, we believe Ironsite is the foundation for what construction becomes in the next decade. We think the systems we're building are the operating system for how the physical world gets built, and will unlock a fundamentally different way of respect for our workforce.

One where craft workers are more valued, more visible, and better paid for the skill they bring, and where the industry finally has the intelligence layer that makes autonomous construction possible.

Both futures start with the same foundation.

The Role

We're hiring a Senior Embedded Firmware Engineer to help own the firmware that runs Ironsite's wearable hardware.

This is a foundational role on the hardware team. The firmware you build has to reliably capture, compress, and upload full days of high-quality first-person video from active jobsites, on ruggedized wearable devices operating in the harshest environments in American industry.

Battery life, image quality, thermal performance, and upload reliability are all firmware problems in this seat. If the firmware breaks, the whole product breaks.

You'll work directly with our hardware, manufacturing, and cloud infrastructure teams to bring devices from initial silicon bring-up through volume manufacturing.

You'll own the camera pipeline, the sensor stack, the OS, the OTA and provisioning infrastructure, and the tuning that makes footage from a hardhat-mounted camera in a dusty jobsite look and behave as good as anything shot in a controlled environment.

This is one of the most technically demanding seats in the company, and one of the highest-leverage.

What You’ll Build

Firmware for our wearable hardware platform.

• Develop embedded software for our wearable devices on platforms like STM32 and Nordic, running Zephyr RTOS.
• Write and maintain drivers and libraries for camera, audio, wireless, IMU, and environmental sensors.
• Own end-to-end sensor bring-up on new hardware revisions, from initial silicon through validated production release.
• Optimize for the constraints that matter in a wearable running an 8-12 hour shift: memory, compute, thermal, and battery.

The camera pipeline.

• Own the imaging pipeline end to end, from sensor driver through ISP tuning to encoded video output.
• Tune ISP parameters (demosaicing, color correction, lens shading correction, spatial and temporal noise reduction, HDR/WDR) for the specific lighting and environmental challenges of construction jobsites, including bright outdoor sun, dark building interiors, and everything in between.
• Analyze and balance image quality tradeoffs: sharpness, dynamic range, noise, artifacts, and encoder efficiency, at the resolutions and framerates our data and AI teams depend on.
• Validate image quality across diverse lighting, motion, and environmental conditions, and build the test infrastructure that makes IQ regressions catchable before they ship.

On-device intelligence.

• Run real-time algorithms and lightweight ML inference on-device, including motion detection, event triggering, and preprocessing that reduces upstream compute and bandwidth costs.
• Partner with our AI research team to move selected inference workloads from the cloud to the edge as models mature.

Reliability, provisioning, and OTA.

• Build reliable, secure infrastructure for device provisioning, over-the-air firmware updates, and telemetry across a fleet growing