The Reality Labs Research Software Team is looking for an Embedded Software Engineer to help bring all-day wearable AI research platforms to life through collaboration and commitment.
Our prototype devices enable breakthrough research in contextualized AI — your firmware captures real-world sensor data, manages on-device compute pipelines, and provides the reliable hardware abstraction that makes research breakthroughs possible.
This role requires a firmware engineer comfortable working across the entire embedded systems spectrum — from low-level MCU peripheral bring-up to SoC-level system integration — rather than specializing in a single domain. You will work across a rich technology stack including Zephyr RTOS on MCUs, AOSP/Linux on Qualcomm SoCs, multi-camera systems (SLAM, RGB, eye tracking), wireless communications (WiFi, BLE, Sub-GHz), IMU-based sensor fusion, and power-optimized embedded architectures for all-day wearable use. We are looking for someone who sees ambiguity as opportunity, nurtures a sense of ownership in themselves and others, and thrives in an honest and considerate environment. We embrace AI-native ways of working — using AI tools as force multipliers to accelerate development, testing, and iteration. We have many exciting problems to solve, and we depend on people who are comfortable with embracing a creative, thoughtful approach to short-term and long-term problem-solving to drive our innovation.
Responsibilities
- Own the design, development, and debugging of firmware, and embedded software, including sensing and imaging systems
- Understand and implement firmware on microcontrollers and SoCs, leverage peripherals, manage power consumption, support boot loaders, and schedule real-time tasks (RTOS)
- Collaborate in a team environment across multiple, research-focused, and engineering disciplines, making the architectural trade-offs required to rapidly deliver firmware solutions, communicating decisions and rationale clearly to a wide range of stakeholders
- Drive firmware architecture and system bring-up across all phases of custom hardware development, including early requirement definition, firmware and embedded system design, proof-of-concept implementation, selection of MCUs and tools, and board bring-up
- Define and champion embedded software development practices across teams and projects, including setting expectations, defining the backlog, and tracking progress of contingent staff
- Provide architectural input in design reviews, influence technical direction across the firmware stack, and serve as a technical expert for the team on complex cross-domain problems for assigned subsystems
- Leverage AI tools and workflows to accelerate firmware development, code generation, testing, and documentation — applying engineering judgment to determine when AI augmentation improves quality, speed, and team efficiency
Minimum Qualifications
- B.S. degree or equivalent experience in Computer Science, Electrical Engineering, or a related field
- 7+ years of software development experience in embedded systems, firmware, or a related field, or a PhD with 4+ years of experience in embedded systems, firmware, or a related field
- 3+ years of embedded software development experience in industry settings
- Experience with embedded software design and programming in C and C++
- Experience with building drivers for custom hardware systems
- Hands-on experience with hardware debugging tools (oscilloscopes, logic analyzers, protocol decoders) and register-level system debugging
- Experience designing firmware solutions from hardware data sheets, including serial protocol (synchronous/asynchronous) interface implementation
- Experience with real-time operating systems (e.g., Zephyr, FreeRTOS, or an equivalent real-time OS)
- Experience in independently architecting embedded systems spanning multiple processors or subsystems (e.g., MCU and SoC integration, multi-core designs) Familiarity with wireless protocol stacks (BLE, Wi-Fi, or proprietary RF)
- Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
- Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
- Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
- Experience working with international manufacturing partners
- AOSP experience outside of apps and in the native environment
- M.S. degree or equivalent experience in Computer Science, Electrical Engineering, or a related field
- Experience in research or prototyping environments where requirements evolve rapidly
- Experience with camera or imaging subsystems (ISP, MIPI CSI/DSI)
- Experience using AI-assisted development tools (code generation, automated testing, AI-powered debugging) to accelerate embedded software workflows
- Experience with SoC bring-up (ARM Cortex-A/M, Qualcomm, NXP, or similar)