GPU-Networking Firmware Engineer at NVIDIA

Beijing, China

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Not SpecifiedCompensation

Mid-level (3 to 4 years)Experience Level

Full TimeJob Type

UnknownVisa

Technology, SemiconductorsIndustries

Requirements

3+ years of relevant professional experience
BS or MS in Computer Science/Computer Engineering/Electrical Engineering or equivalent experience
Proficient knowledge of C
Excellent understanding of embedded SW and real-time programming
Strong analytical, creative, debugging and problem-solving skills
Meticulous and comfortable with multitasking in a dynamic environment with shifting priorities and changing requirements
Strong programming skills in Python
An excellent teammate with good social skills

Responsibilities

Design and implement new features in the core of NVIDIA GPU firmware
Collaborate with architecture and different software design teams throughout the software development lifecycle
Work in Pre & Post-silicon development environments of next-generation NVIDIA GPU products
Gain a deep understanding of system debugging, networking technology, and stacks, as well as the HW/FW/SW relationship
Innovate! Bring NVIDIA's FW switching products to shine in customer's view
Collaborate with other NVIDIA R&D teams around the globe

Skills

Key technologies and capabilities for this role

CPythonEmbedded SoftwareReal-time ProgrammingAssemblyNetwork ProtocolsFirmware DevelopmentDebugging

Questions & Answers

Common questions about this position

What are the required qualifications for the GPU-Networking Firmware Engineer role?

Candidates need 3+ years of relevant professional experience, a BS or MS in Computer Science, Computer Engineering, or Electrical Engineering (or equivalent), proficient knowledge of C, excellent understanding of embedded SW and real-time programming, strong analytical, creative, debugging and problem-solving skills, strong programming skills in Python, and must be an excellent teammate with good social skills.

What skills will help me stand out for this position?

Knowledge of network protocols, assembly programming and debugging hands-on experience, background in Linux internals, scripting abilities in Python and Bash, and motivation to learn and constantly improve processes and tools will make you stand out.

What is the work environment like at NVIDIA for this role?

The work environment is dynamic, exciting, and fast-paced, with dedicated engineers around the globe and collaboration with other NVIDIA R&D teams worldwide.

Is the salary or compensation specified for this position?

This information is not specified in the job description.

What kind of work arrangement or location is required?

This information is not specified in the job description.

NVIDIA

Designs GPUs and AI computing solutions

About NVIDIA

NVIDIA designs and manufactures graphics processing units (GPUs) and system on a chip units (SoCs) for various markets, including gaming, professional visualization, data centers, and automotive. Their products include GPUs tailored for gaming and professional use, as well as platforms for artificial intelligence (AI) and high-performance computing (HPC) that cater to developers, data scientists, and IT administrators. NVIDIA generates revenue through the sale of hardware, software solutions, and cloud-based services, such as NVIDIA CloudXR and NGC, which enhance experiences in AI, machine learning, and computer vision. What sets NVIDIA apart from competitors is its strong focus on research and development, allowing it to maintain a leadership position in a competitive market. The company's goal is to drive innovation and provide advanced solutions that meet the needs of a diverse clientele, including gamers, researchers, and enterprises.

Santa Clara, CaliforniaHeadquarters

1993Year Founded

$19.5MTotal Funding

IPOCompany Stage

Automotive & Transportation, Enterprise Software, AI & Machine Learning, GamingIndustries

10,001+Employees

Benefits

Company Equity

401(k) Company Match

Risks

Increased competition from AI startups like xAI could challenge NVIDIA's market position.

Serve Robotics' expansion may divert resources from NVIDIA's core GPU and AI businesses.

Integration of VinBrain may pose challenges and distract from NVIDIA's primary operations.

Differentiation

NVIDIA leads in AI and HPC solutions with cutting-edge GPU technology.

The company excels in diverse markets, including gaming, data centers, and autonomous vehicles.

NVIDIA's cloud services, like CloudXR, offer scalable solutions for AI and machine learning.

Upsides

Acquisition of VinBrain enhances NVIDIA's AI capabilities in the healthcare sector.

Investment in Nebius Group boosts NVIDIA's AI infrastructure and cloud platform offerings.

Serve Robotics' expansion, backed by NVIDIA, highlights growth in autonomous delivery services.

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