System Software / Embedded Engineer

Jobgether; United States; Remote; USD 120,000 - 190,000; Full time

Benefits offered by this job

Competitive compensation

Comprehensive benefits

Flexible spending options

Employee recognition

Collaborative environment

Innovative technical work

Flexible collaboration

Professional growth

Job summary

Jobgether is seeking an System Software / Embedded Engineer to design, develop, validate, and optimize platform software for AI inference systems. You will work on firmware, BSPs, device drivers, and Linux kernel modules, collaborating with hardware and silicon teams to ensure reliable operation.

The role involves performance profiling, debugging, and power optimization across data-center AI platforms, with opportunities to travel to partner sites as needed.

Qualifications

• 5+ years of experience in low-level systems software and embedded firmware.
• Experience with Linux kernel drivers and embedded Linux.
• Experience with SoC bring-up and hardware debugging.

Responsibilities

• Develop system-level software for AI inference platform.
• Bring up embedded Linux kernel drivers and BSPs.
• Debug and validate platform software with hardware teams.
• Develop tools for performance profiling and diagnostics.
• Optimize power and performance for AI inference systems.

Skills

Embedded software

C/C++ programming

Python scripting

Debugging

Cross-functional collaboration

Technical communication

Education

Bachelor's or Master's in Electrical Engineering or Computer Science

Tools

JTAG debuggers

Logic analyzers

Oscilloscopes

Job description

Accountabilities:

As a System Software / Embedded Engineer, you will contribute to the design, development, validation, and optimization of platform software for advanced AI inference systems. Your responsibilities will include:

• Develop system-level software: Gather requirements, design, implement, and maintain low-level services, tools, and supporting tests for AI inference platform software.
• Build and debug embedded systems: Work on firmware, board bring-up, bootloaders, board support packages (BSPs), device drivers, and Linux kernel modules.
• Support hardware and silicon bring-up: Collaborate with hardware, silicon, and validation teams to bring up, debug, and validate platform software on AI inference systems.
• Enable hardware/software co-design: Work directly with hardware and silicon engineers to troubleshoot integration challenges and ensure software and hardware components operate reliably together.
• Develop debugging and profiling capabilities: Create and improve tools for system analysis, diagnostics, performance profiling, and root-cause investigation.
• Optimize performance and power consumption: Analyze system behavior and implement improvements to maximize inference platform efficiency, responsiveness, and reliability.
• Work with low-level hardware interfaces: Debug and integrate components using interfaces and protocols such as PCIe, I2C, SPI, and JTAG.
• Ensure production-quality delivery: Develop robust, maintainable software and comprehensive tests that support platform validation and deployment in data center environments.
• Collaborate across engineering disciplines: Coordinate with software, hardware, silicon, and validation teams to resolve technical issues and deliver platform milestones.
• Support external engineering activities: Travel occasionally to partner, customer, or contract manufacturing sites when required; travel is not mandatory.

Requirements:

The ideal candidate combines strong embedded software engineering expertise with hands-on hardware debugging experience and the ability to work effectively across multiple engineering disciplines. Key qualifications include:

• Professional experience: At least 5 years of experience developing low-level systems software, embedded software, firmware, and engineering tools for high-performance computing systems deployed to data center customers.
• Linux and embedded systems: Practical experience bringing up and debugging complex Linux-based systems at the kernel and driver levels, including embedded Linux, device drivers, and/or real-time operating system (RTOS) environments.
• Silicon and SoC experience: Experience with system-on-chip or silicon bring-up is highly desirable.
• Programming expertise: Advanced proficiency in C and C++, along with working proficiency in Python, Bash/Shell, or related scripting languages. Rust experience is an advantage.
• Hardware debugging: Comfort working directly with hardware, interpreting schematics and datasheets, and troubleshooting with tools such as JTAG debuggers, logic analyzers, and oscilloscopes.
• Hardware interfaces: Familiarity with low-level interfaces and protocols such as PCIe, I2C, SPI, and JTAG.
• AI and data center environments: Familiarity with AI inference frameworks and data center deployment or management environments is preferred.
• Education: A bachelor's or master's degree in Electrical Engineering, Computer Science, or a related technical discipline.
• Cross-functional collaboration: Ability to work effectively with hardware, silicon, validation, and software teams to solve complex integration problems.
• Communication skills: Excellent technical communication skills, including the ability to explain complex concepts, debugging findings, and proposed solutions clearly.
• Adaptability and ownership: A self-motivated, adaptable approach to problem-solving, with the ability to take ownership of technical challenges and deliver results in a fast-paced startup environment.
• Commitment to engineering excellence: Strong attention to quality, integrity, continuous improvement, and collaborative problem-solving.

Benefits:

• Competitive compensation: A competitive compensation package.
• Comprehensive benefits: Benefits designed to support employees and their families.
• Flexible spending options: Flexible spending benefits to support individual needs.
• Employee recognition: Recognition programs that acknowledge contributions and achievements.
• Collaborative environment: The opportunity to work with talented engineers across software, hardware, and silicon disciplines.
• Innovative technical work: The opportunity to contribute to high-performance, low-power AI inference systems and emerging generative AI technologies.
• Flexible collaboration: A distributed working environment with team members across North America and Europe.
• Professional growth: Opportunities to tackle complex engineering challenges and contribute to ambitious technology development.