The posting
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 are 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. The systems we're building will be the operating system for how the physical world gets built. We see a future 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 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 role. 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 roles 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 from thousands to hundreds of thousands of devices. Design the firmware architecture and test infrastructure that makes fleet updates safe, staged, and recoverable. Own the debugging tools, logging infrastructure, and observability that let us diagnose issues on devices deployed in the field.
Hardware and manufacturing partnership. Collaborate with hardware and manufacturing engineers across the full product lifecycle, from initial architecture and prototype bring-up through DFM, DFT, and volume production. Design firmware alongside manufacturing test procedures. Programming stations, functional test, and factory calibration are firmware problems as much as manufacturing problems. Support new hardware revisions with rapid firmware iterations, and ensure firmware releases stay tightly aligned with the manufacturing cadence.
What We're Looking For
Required 6+ years of hands-on experience shipping embedded firmware on production hardware, with at least one full product lifecycle delivered in wearables, cameras, or IoT devices at real volume. Deep expertise in C and C++ for embedded systems with real resource constraints. You've written firmware that lived within tight memory, compute, and power budgets. Deep experience with camera and imaging pipelines, including sensor drivers, ISP tuning, and image quality analysis. This is not optional. You've owned an image pipeline in production and can speak concretely about what you tuned, what you fixed, and what tradeoffs you made. Strong understanding of ISP core blocks: demosaicing, color correction, lens shading correction, spatial and temporal noise reduction, and HDR/WDR performance. Hands-on experience with at least one industry-standard microcontroller platform (STM32, nRF, ESP32, or similar) and one embedded RTOS (Zephyr, FreeRTOS, or similar). Comfortable reading schematics and datasheets, and using standard hardware lab tools (oscilloscope, logic analyzer, JTAG, protocol analyzers) to debug hardware-software integration issues. Systems thinking across the full embedded stack. From silicon to the cloud, you understand how firmware decisions propagate up and down. A background in Electrical Engineering, Computer Engineering, or a related field, or the equivalent experience.
Strongly preferred Experience shipping wearable products at consumer volumes (Fitbit, Oura, Whoop, GoPro, Bose, Apple, Meta, Snap, or similar). Experience with wireless connectivity stacks (BLE, Wi-Fi, LTE, or similar) and their power and reliability implications. Experience with power management design and low-power firmware techniques. Experience shipping OTA update systems for large device fleets.
Nice to have Experience with on-device ML inference, including quantization, model deployment on edge accelerators, and inference optimization for constrained platforms. Experience with high-speed video encoding pipelines (H.264, H.265, AV1) and the codec-side tradeoffs. Experience with audio processing pipelines (even though we don't capture audio on our devices, adjacent experience often transfers). Experience contributing to Zephyr OS upstream or maintaining fork-level customizations.
What Success Looks Like
First 90 days. You know our hardware platform cold, including the sensor stack, the ISP, the RTOS configuration, and the manufacturing test infrastructure. You've shipped your first meaningful firmware improvement to production devices. First 6 months. You've owned a major firmware initiative end to end, whether it's a next-generation camera bring-up, a fleet-wide OTA architecture improvement, or a battery life optimization that materially extends shift capacity. Your work is running on every deployed device. First 12 months. You're the internal authority on firmware at Ironsite. Our devices are more reliable, more efficient, and easier to update because of you. When we scale from thousands of devices to hundreds of thousands, we do it because the firmware you built holds up.
Location, Compensation, & Perks
San Francisco Bay Area (on-site) Base salary: $200k-$300k per year, commensurate with experience Significant early-stage equity Full benefits including health, dental, vision, and 401(k) with 6% match Daily catered lunch Office in San Francisco, next to Oracle Park and the Caltrain
Final compensation is determined by experience, location, and level.
Why This Role
Every category-defining hardware company has a firmware engineer who was the reason the product actually worked in the real world. Not because they wrote the fanciest code, but because they cared obsessively about the last 5% of image quality, the last 30 minutes of battery life, and the one edge case that would have caused a fleet-wide failure at scale.
Ironsite is at that moment. We have the product, the customers, the funding, the manufacturing partnerships, and a hardware roadmap that scales into hundreds of thousands of units. What we need is the firmware engineer who is going to make sure the devices actually deliver on what our data, AI, and customer promises require.
If you've spent your career shipping camera firmware on wearables, and you're ready to do it again on a product that matters more than most, we want to talk.
