# ASIC Firmware Engineer, Modeling

**Company:** [OpenAI](https://hotfix.jobs/companies/openai)
**Location:** San Francisco, CA
**Role:** Embedded Engineering
**Salary:** $226k – $445k/yr
**Experience:** 5+ years
**Skills:** C++, Rust, Embedded Systems, Rtos, Hardware Drivers, Hw/Sw Co-Design, Uart, I2C, Spi, Arm
**Posted:** 2026-02-03

> Develop firmware and modeling software for OpenAI's AI accelerator, including drivers, low-latency embedded code, and functional models for SoC simulation. Requires 5+ years in embedded software, strong C/C++/Rust skills, and hardware experience.

## Job Description

## Responsibilities
- Design and implement drivers for hardware peripherals, including those related to AI chips.
- Design and implement functional software models to simulate SoC uncore logic and enable FW testing against the model.
- Design and implement low-latency and high throughput embedded SW to manage HW resources.
- Work with adjacent software and hardware teams to implement requirements, debug issues and shape future generations of the hardware.
- Collaborate with vendors to integrate their technologies within our systems.
- Bring up and debug firmware/driver on new platforms.
- Come up with processes and debug issues raised in the field.
- Set up monitoring, integration testing and diagnostics tools.

## Qualifications
- **5+ years** of experience working in embedded SW space.
- Ability to thrive in ambiguity and learn new technologies.
- Strong programming skills in **C/C++** and/or **Rust**.
- Experience developing high throughput, low latency and multi-threaded code.
- Experience working with real time operating systems (**RTOS**).
- Experience developing hardware drivers and working with hardware.
- Experience with **HW/SW co-design**.
- Knowledge of common embedded protocols, e.g. **UART**, **I2C**, **SPI**, etc.
- Knowledge of microprocessor and common **ARM** architectures (e.g. **AMBA**) is a plus.
- Knowledge of **PCIe**, **ethernet** and other high BW communication protocols is a plus.
- Experience with **GPUs** or other compute hardware is a plus.
- Experience deploying large compute clusters is a plus.

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