Used Tools & Technologies
Not specified
Required Skills & Competences
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Python @ 7
Leadership @ 4
Communication @ 7
Debugging @ 4
System Architecture @ 4
GPU @ 4
Deep Learning @ 7
AI @ 4
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern deep learning — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, we are increasingly known as “the AI computing company.” We are looking to grow our company and establish teams with the most thoughtful people in the world.
We’re looking for a highly motivated, creative Factory System Software and Diagnostics Integration engineer to join the Datacenter Platform Software team. You will play a crucial role in coordinating factory projects, guiding cross-functional teams, and collaborating with stakeholders to ensure the successful delivery of firmware, software and diagnostics that align with business objectives, as well as analyzing, evaluating, and improving factory processes. This role is for NVIDIA's GPU or DPU based products.
Responsibilities
- Lead Factory Validation projects from software, firmware and diagnostics perspectives, ensuring successful implementation, integration, and standardization across multiple locations.
- Lead the integration and handover of the software, firmware and diagnostics for all products.
- Act as a primary consultant, offering strategic direction and leadership to the engineering teams.
- Engage with ODMs and cross-functional teams to collect and analyze factory requirements, delivering solutions that meet both business and operational needs.
- Analyze factory processes, systems, and workflows to identify areas for improvement and optimization.
- Develop and maintain detailed documentation, including system requirements, processes and standard operating procedures (SOPs). Collaborate across teams to design, configure, and implement changes to factory ensuring seamless integration and minimal disruption.
- Perform system testing, validation, and fixing to ensure exact functionality and alignment with factory requirements.
- Monitor, collect, and analyze data to identify and address issues, and propose solutions to enhance system reliability and efficiency.
- Collaborate with vendors and external partners to evaluate, select, and implement new factory systems or software/firmware upgrades.
Requirements
- 5+ years of relevant experience.
- BS, MS, or PhD in EE/CS or related field (or equivalent experience).
- 2–5 years of experience working as an Integration Engineer in factory settings.
- Strong knowledge of server manageability, bring up and deployment in data centers. Proven understanding of firmware and diagnostics for x86 and ARM servers.
- Experience working with ODM/OEMs to deliver quality servers.
- Strong and demonstrable skill in Python, C/C++, and shell scripting.
- Experience programming and debugging for GPU platforms.
- Excellent written and oral communication skills, strong teamwork and work ethics, self-starter with hands-on coding ability and commitment to delivering quality work.
Ways to stand out
- Worked on factory integration or hardware bring-up projects.
- Hands-on experience with x86 or ARM system architecture.
Compensation & Benefits
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4. You will also be eligible for equity and benefits: https://www.nvidia.com/en-us/benefits/.
Other information
- Applications for this job will be accepted at least until March 21, 2026.
- This posting is for an existing vacancy.
- NVIDIA uses AI tools in its recruiting processes.
- NVIDIA is an equal opportunity employer and is committed to fostering a diverse work environment.