Network RDMA Algorithms Architect

Reposted 9 Hours Ago
Be an Early Applicant
2 Locations
In-Office
Junior
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
The Role
Design and research RDMA load balancing and congestion-control algorithms for data-center networking. Build and validate algorithms in simulation and on real hardware, collaborate across teams to develop proofs-of-concept, and advance next-generation ConnectX/SPC-X networking solutions.
Summary Generated by Built In

Come be part of NVIDIA, the industry leader in AI Data Centers. We are now innovating the future of data center, and defining the next generation of networking solutions. Our team is dedicated to pushing boundaries and overcome the challenges involved in providing high performance data centers. As a Network RDMA Algorithms Architect, you'll contribute to our creative and cooperative setting, focusing on the ConnectX network adapter, SPC-X end to end solution and more exciting technologies.

What you'll be doing:

  • Conduct research and analysis on networking solution and end to end algorithms.

  • Work with a creative and experienced team to outline the next generation of our RDMA load balance and congestion control algorithms.

  • Work on simulation environment and on real HW systems

  • Engage with other research teams to develop Proof of Concepts using our technology.

What we need to see:

  • 2+ years of experience.

  • B.Sc. in Electrical Engineering or Computer Engineering.

  • High motivation to learn and explore new fields.

  • Proven problem-solving skills.

  • Excellent interpersonal skills.

  • Knowledge and understanding of compute and networking systems is an advantage.

  • Passion and attention to detail in building with a high focus on building quality.

Ways to stand out from the crowd:

  • Passion and love for system architecture, including CPU/GPU/Memory/Storage/Networking.

  • Background with AI workloads.

  • Background with networking.

  • Experience in the development of simulation environments.

NVIDIA values diversity in employees. We are an equal opportunity employer, not discriminating in hiring or promotions based on various protected characteristics.

Skills Required

  • 2+ years of experience
  • B.Sc. in Electrical Engineering or Computer Engineering
  • High motivation to learn and explore new fields
  • Proven problem-solving skills
  • Excellent interpersonal skills
  • Passion and attention to detail with high focus on building quality
  • Knowledge and understanding of compute and networking systems
  • Passion for system architecture (CPU/GPU/Memory/Storage/Networking)
  • Background with AI workloads
  • Background with networking
  • Experience developing simulation environments

NVIDIA Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.

  • Equity Value & Accessibility Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
  • Healthcare Strength Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
  • Retirement Support Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.

NVIDIA Insights

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The Company
HQ: Santa Clara, CA
21,960 Employees
Year Founded: 1993

What We Do

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 AI — 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, NVIDIA is increasingly known as “the AI computing company.”

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