Systems Software Engineer, CPU Manageability Stack
Overview
- Added in 30 days
- 658
- At this company, still open
Skills named in this posting
- Python
- Linux kernel
- Device drivers
- QEMU
- Virtualization
NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. We are building industries leading CPUs for embedded, automotive and data center verticals to harness the full potential of our versatile and performance GPUs. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.
We are now actively looking for energetic, enthusiastic and technologically savvy engineers to join the Chips System Software team. Here we architect and develop the boot firmware for the flagship CPUs which are the core components for high-compute platforms for automotive, datacenter and other critical applications. The best candidates will have excellent C and Python programming skills, a thorough understanding of operating systems and kernel programming, a good understanding of hardware architecture, and excellent communication and planning skills.
What you'll be doing:
• As a member of the Tegra Core Firmware Team, you will build and develop Manageability Software stack environment.
• Apply your strong communication skills to develop software, drive ideas, and analyze documents, ensuring flawless communication of our technology to both internal and external audiences.
• Participate in embedded bare-metal development for Tegra chips and connect these activities to server management protocols and standards.
• Collaborate closely with hardware architecture teams, finding opportunities to improve our architecture and make it more performant across generations.
• Develop partnerships with team members internally and externally, as collaboration is key in our engineering teams!
What we need to see:
• 5+ years of experience with BS or MS degree in Computer Engineering, Computer Science, or a related field.
• Outstanding C and Python programming abilities.
• A strong desire to continuously improve processes and tools for a productivity at speed of light through AI tools.
• Working experience with server management protocols such as IPMI, MCTP, and PLDM is a definite plus.
• Strong understanding of multicore hardware, operating systems build, concurrency, virtual memory, caching, interrupts, device drivers, and real-time programming
• Detailed and extensive experience with Linux kernel software is required
• Excellent interpersonal skills.
Ways to stand out from the crowd:
• Experience analyzing, debugging, and tuning the performance of complex system software stacks.
• Knowledge and understanding of OpenBMC and virtualization platforms (KVM, QEMU).
• Working experience with AI tools such as Codex, creating agentic AI tools
• Proficiency creating skills with continuos refinement.
• Deep understanding of system-level architecture, such as topologies, interconnects, memory hierarchy, interrupts, and memory-mapped IO.
Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family www.nvidiabenefits.com/
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Original posting: jobs.nvidia.com
RISC-V ecosystem
NVIDIA Corporation in the RISC-V ecosystem
RISC-V International: Premier Board
Founded in 1993, NVIDIA is an AI computing company. The company is headquartered in Santa Clara, California.
- NVIDIA is bringing CUDA platform support to RISC-V, i.e. allowing a RISC-V CPU to host CUDA GPU applications
- Publicly credited the RVA23 profile as the enabler: "We wouldn't have considered porting CUDA to RISC-V without it"
- Active in RISC-V International profile/standards work and a frequent presence in RISC-V ecosystem coverage
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