System Software​/Embedded Engineer

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.

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.

• 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…