Embedded Software Engineer

Summary:

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.

Required Skills:

Embedded Software Engineer Responsibilities:

1. Own the design, development, and debugging of firmware, and embedded software, including sensing and imaging systems

1. Understand and implement firmware on microcontrollers and SoCs, leverage peripherals, manage power consumption, support boot loaders, and schedule real-time tasks (RTOS)

1. 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

1. 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

1. Define and champion embedded software development practices across teams and projects, including setting expectations, defining the backlog, and tracking progress of contingent staff

1. 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

1. 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:

Minimum Qualifications:

1. B.S. degree or equivalent experience in Computer Science, Electrical Engineering, or a related field

1. 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

1. 3+ years of embedded software development experience in industry settings

1. Experience with embedded software design and programming in C and C++

1. Experience with building drivers for custom hardware systems

1. Hands-on experience with hardware debugging tools (oscilloscopes, logic analyzers, protocol decoders) and register-level system debugging

1. Experience designing firmware solutions from hardware data sheets, including serial protocol (synchronous/asynchronous) interface implementation

1. Experience with real-time operating systems (e.g., Zephyr, FreeRTOS, or an equivalent real-time OS)

1. Experience in independently architecting embedded systems spanning multiple processors or subsystems (e.g., MCU and SoC integration, multi-core designs)

Preferred Qualifications:

Preferred Qualifications:

1. Familiarity with wireless protocol stacks (BLE, Wi-Fi, or proprietary RF)

1. Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)

1. Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)

1. Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies

1. Experience working with international manufacturing partners

1. AOSP experience outside of apps and in the native environment

1. M.S. degree or equivalent experience in Computer Science, Electrical Engineering, or a related field

1. Experience in research or prototyping environments where requirements evolve rapidly

1. Experience with camera or imaging subsystems (ISP, MIPI CSI/DSI)

1. Experience using AI-assisted development tools (code generation, automated testing, AI-powered debugging) to accelerate embedded software workflows

1. Experience with SoC bring-up (ARM Cortex-A/M, Qualcomm, NXP, or similar)

Public Compensation:

$184,000/year to $257,000/year + bonus + equity + benefits

Industry: Internet

Equal Opportunity:

Meta is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Meta participates in the E-Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.

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