Software Engineer, Embedded Systems

Meta Careers; Menlo Park, New York (CA, NY); Vor Ort; USD 190.000 - 230.000; Vollzeit

Zusammenfassung

Meta is seeking an embedded systems engineer to convert deep domain expertise into high-quality training signals for frontier coding models. The role involves hands-on engineering to analyze low-level challenges, build rigorous evaluations, and generate trajectory data for model training, with the primary deliverable being an optimized model rather than a standard feature.

This fast-paced role leverages systems-level expertise to transform software engineering workflows and contribute to the

Qualifikationen

• Bachelor's degree or equivalent practical experience in Computer Science/Engineering.
• 8+ years of embedded software engineering for resource-constrained systems, in C/C++.
• Experience across multiple embedded platforms, RTOS environments, and Linux or AOSP on application processors.
• Experience writing device drivers or hardware abstraction layers for peripherals (sensors, power management ICs, displays, I2C/SPI/UART/USB).
• Experience building telemetry, logging, or monitoring infra for embedded systems at scale.
• Experience automated test infra for embedded systems (HIL, on-device automation, or CI pipelines).
• Experience debugging cross-layer embedded issues with JTAG, logic analyzers, oscilloscopes, or static analysis tools.
• Demonstrated ability to integrate AI tools to optimize workflows and drive measurable impact.
• Experience adhering to responsible, ethical AI practices (risk assessment, bias mitigation, quality reviews).
• Ongoing AI skill development (prompt/context engineering, agent orchestration) and staying current with AI tech.
• Experience with AI coding assistants and evaluating outputs for correctness, safety, and adherence to embedded standards.

Kenntnisse

C/C++

Embedded systems

RTOS

Linux/AOSP

Device drivers

Telemetry/Logging

Test automation

AI tooling integration

Ethical AI practices

AI skill development

AI coding assistants usage

Ausbildung

Bachelor's degree in Computer Science/Computer Engineering or equivalent practical experience

Tools

I2C

SPI

UART

USB

JTAG debuggers

Logic analyzers

Oscilloscopes

Static analysis tools

CI pipelines

Hardware-in-the-loop testing

Jobbeschreibung

The Device & Embedded group within Applied AI focuses on enhancing artificial intelligence models that support low-level system development, including bootloaders, operating systems, kernels, drivers, and intermediate system services. We are seeking an embedded systems engineer to convert deep domain expertise into high-quality training signals for Meta's frontier coding models. In this role, you will analyze complex low-level engineering challenges from this domain, construct rigorous evaluations and trajectory data for model training, and identify areas requiring model improvement. While the position involves direct, hands‑on engineering, the primary deliverable is an optimized model rather than a standard product feature. This fast‑paced role is ideal for engineers who wish to leverage their systems‑level expertise to transform software engineering methodologies.

• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience8+ years of experience in embedded software engineering, including development in C or C++ for resource‑constrained systems
• Experience developing and debugging software across multiple embedded platforms, including RTOS environments and Linux or AOSP on application processors
• Experience writing device drivers or hardware abstraction layers for peripherals such as sensors, power management ICs, displays, or communication buses (I2C, SPI, UART, USB)
• Experience building telemetry, logging, or monitoring infrastructure to track embedded system health and diagnose production issues at scale
• Experience developing automated test infrastructure for embedded systems, including hardware-in-the-loop testing, on‑device automation, or CI pipelines targeting embedded targets
• Experience debugging complex cross‑layer embedded issues using tools such as JTAG debuggers, logic analyzers, oscilloscopes, or static analysis tools
• Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
• Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
• Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
• Experience working with AI coding assistants and evaluating their output for correctness, safety, and adherence to embedded development standards
• Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
• Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
• kernel internals (Android or Linux or RTOS), plus device driver development across common subsystems
• Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
• Experience collaborating with silicon or chipset vendors on firmware bring‑up, reference design adaptation, and hardware errata mitigation
• Experience in leveraging AI tools to accelerate embedded development workflows, automate diagnostics, or improve code quality and test coverage