Lead Embedded Firmware Engineer

OSI Engineering, Inc.; Palo Alto (CA); On-site; USD 300,000 - 350,000; Full time

Job summary

OSI Engineering, Inc. is seeking a senior firmware leader to architect and build the distributed-compute firmware stack for a next-gen neurotechnology wearable.

You will own end-to-end firmware from board bring-up to production, directing internal engineers and external partners while staying involved in hands-on bring-up and verification. Your track record includes 10+ years in embedded firmware, strong C/C++, and deep RTOS expertise, plus experience with multi-MCU systems and secure updates.

Qualifications

• 10+ years of embedded firmware engineering with at least one battery-powered product.
• Proven track record leading firmware teams across internal and external partners.
• Deep expertise with embedded RTOSes and bare-metal ARM Cortex-M and C/C++.
• Hands-on in the lab: schematics reading, JTAG/SWD, logic analyzers, and bring-up.
• Ability to own hardware bring-up and drive end-to-end product readiness.

Responsibilities

• Lead firmware architecture across distributed compute platform, select RTOS, define task structure and protocols.
• Own runtime hosting subsystems: audio DSP, camera pipeline, biosignals acquisition within CPU/memory budgets.
• Drive media and connectivity MCU pipeline: camera, audio, wake-word, Wi-Fi, onboard logging.
• Develop low-power firmware for always-on MCU with state machines, privacy, thermal control.
• Establish firmware engineering practices: repos, reviews, reproducible builds, OTA, telemetry, test, rollback.
• Hire, develop, and lead firmware team; collaborate with hardware and silicon teams.
• Ship first-generation product by year-end; oversee production and field support.

Skills

Firmware architecture

Embedded leadership

C/C++

RTOS expertise

Board bring-up

Tools

JTAG/SWD

Logic analyzers

MCU toolchains

Job description

We're a stealth-stage neurotechnology and brain-computer interface (BCI) startup building a noninvasive, head-worn wearable that decodes neural signals with a fidelity once reserved for surgical implants. Paired with our own foundation model for neural data, the platform is designed to give people a direct, real-time link between mind and machine — a new category of device, not another gadget or productivity tool.

You will lead firmware architecture and development for the distributed-compute platform that makes this possible: media and connectivity, biosignal acquisition, and the always-on subsystems that manage power, privacy, and thermal behavior. With little firmware infrastructure in place today, you will build the internal team and engineering practices from the ground up while directing our existing engineering firm and manufacturing partners — and you'll stay personally in the details throughout, reviewing schematics, working the bench, and driving bring-up yourself, not just attending reviews. Your first goal is to ship a first-generation launch within the year; from there you'll own software readiness through production and field support as we scale. Separate teams own the algorithms and models — your team owns their integration and reliable execution on the device.

• Lead/architect firmware across the distributed-compute platform: RTOS choice, task structure, inter-processor protocols, OTA, and time sync.
• Own the runtime that hosts every subsystem — audio DSP, camera capture pipeline, biopotential acquisition — through specified interfaces with each subsystem lead.
• Own the media and connectivity MCU pipeline: camera capture, audio runtime, wake-word, Wi-Fi streaming, and onboard logging, concurrently within strict CPU and memory budgets.
• Drive low-power firmware on the always-on MCU: state machines for standby, assist, and continuous modes; hardware-enforced privacy; thermal throttling.
• Build the multi-MCU time-sync layer that lets us correlate EEG, audio, and camera data downstream.
• Establish the firmware engineering practices that scale: company-controlled repositories, code review, and reproducible builds; build and release pipelines; on-device telemetry; automated test; OTA with safe rollback; field debug tooling.
• Establish the device threat model and security requirements, then own secure boot, signed updates, device provisioning, protection of signing keys and sensor data, and vulnerability remediation.
• Partner with the EE lead on hardware bring-up and boot path, and with the reliability lead on field telemetry, error handling, and diagnostic surfaces.
• Bring up ASICs and boards in collaboration with the EE and silicon teams, through to production and field support.
• Work with manufacturing partners on flashing, calibration support, factory diagnostics, and software traceability; prepare recovery from interrupted or failed field updates before launch.
• Hire, develop, and lead the firmware team as we scale to production — directing internal engineers and external partners while owning trade-offs and product decisions rather than only executing a scope someone else defined.
• Ship the product by the end of year.

Responsibilities

• 10+ years of embedded firmware engineering, with at least one shipped, battery-powered consumer product where you owned firmware architecture end-to-end — from board bring-up through production and field support.
• A track record building and leading a firmware organization: hiring engineers, directing delivery across internal teams and external/manufacturing partners, and staying involved in consequential technical decisions.
• Deep expertise across embedded RTOSes and bare-metal ARM Cortex-M, with hands-on delivery across at least two ecosystems (e.g., Zephyr, FreeRTOS, ESP-IDF, ThreadX, NuttX) and strong C/C++.
• Hands-on experience hosting real-time DSP runtimes alongside wireless connectivity on resource-constrained MCUs — integrating algorithms owned by other teams within tight CPU and memory budgets.
• Strong background in multi-radio coexistence (Wi-Fi + BLE), low-power state-machine design, and OTA with safe rollback.
• Experience establishing or substantially improving build, test, validation, and release practices, so internal and partner contributions are reproducible, testable, and production-ready.
• Practical experience delivering and maintaining secure devices — software updates, credentials, and vulnerability handling — and directing specialist security review where needed.
• Genuinely hands-on and comfortable in the lab: reading schematics, using JTAG/SWD, logic analyzers, and protocol sniffers, and personally driving bring-up from first power-on through end-to-end functional demos. This is not a role for someone who delegates all technical work and attends only the review meetings.
• A career that started in a hands-on engineering role rather than management — you've since grown into leading people and thinking strategically about the product, but you still go get in the details yourself when it matters.

Preferred Skills

• Deploying neural network inference to low-power MCUs or dedicated AI accelerators — model conversion, quantization, runtime integration.
• Familiarity with on-device inference frameworks and edge AI runtimes.
• Custom AI accelerator silicon, neuromorphic compute, or in-memory-compute platforms.
• On-device wake-word or always-on voice activation engines.
• Integrating biopotential acquisition over standard sensor buses.
• Experience with wearables, biosignal sensing, audio, or other continuous sensor pipelines.
• Familiarity with Qualcomm Snapdragon or comparable application processors and companion microcontrollers, and deploying models within limited power and memory budgets.

Owen Williamson

408.550.2800 x127

Salary Range: $300k–$350k/y (DOE), plus equity and full benefits (401(k) with company match, health insurance, flexible PTO)