System Software / Embedded Engineer in United States at Jobgether

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a System Software / Embedded Engineer based in the United States.

The System Software / Embedded Engineer will develop and optimize low-level software powering next-generation AI inference platforms. This role sits at the intersection of hardware, silicon, firmware, and systems engineering, contributing to high-performance, energy-efficient infrastructure for multimodal generative AI. You will design system-level services, development tools, and testing capabilities while supporting hardware bring-up and platform validation. Working closely with hardware, silicon, and validation teams, you will help ensure robust, production-ready software for demanding data center environments. Your work will also focus on debugging, profiling, and optimizing system performance and power consumption. This is an opportunity to contribute to cutting-edge AI infrastructure within a fast-paced, collaborative engineering environment based in Sunnyvale, California, with flexibility for remote collaboration across North America and Europe.

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.