NVIDIA Corporation

Senior Solutions Architect, AI Performance Engineering

NVIDIA Corporation • $184K — $356K *
Santa Clara, CA 95051In-Person
Consumer Technology
8 - 10 years of experience
Today
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Job Overview by Ladders

Qualifications

  • BSc/MSc/PhD in Computer Science, Electrical Engineering, Physics, Mathematics, or a related field.
  • 8+ years of hands-on experience in ML/DL performance engineering focusing on GPU efficiency.
  • Proficiency in C, C++, or Python with strong Linux skills.
  • Solid understanding of software development and algorithms.
  • Strong mathematical fundamentals, particularly in linear algebra and numerical methods.
  • Experience in parallel programming and high-performance computing, especially GPU programming.
  • Familiarity with distributed communication optimization and open-source libraries for large-scale model training.

Responsibilities

  • Engage with AV application engineers to address current and future challenges.
  • Develop and enhance parallel algorithms and data structures for performance optimization.
  • Collaborate with NVIDIA teams to influence the development of next-gen architectures and software platforms.
  • Optimize high-performance operators through GPU kernel and compiler optimizations.
  • Improve communication for AI workloads using NVIDIA's communication tools and open-source solutions.
  • Study interconnect topologies and develop efficient data transfer strategies to enable compute-communication overlap.

Benefits

  • Equity opportunities.
  • Comprehensive health benefits.
  • Flexible work arrangements.
  • Employee wellness programs.
  • Access to cutting-edge technology and resources.
Full Job Description
We are looking for a Solutions Architect with a performance engineering background who can help our most sophisticated Autonomous Vehicles and Robotics customers accelerate Physical AI workloads using NVIDIA's full-stack technologies! As part of the Automotive Solutions Architecture team, we work with some of the most innovative accelerated computing platforms focused on the development and test of Autonomous Vehicles. We dive deep into customer projects to solve performance bottlenecks. We use insights from workloads to guide next-generation NVIDIA hardware and software. If you are driven by innovation and ambition, this is the team for you!

What you'll be doing:
  • Engaging directly with key AV application engineers to understand the current and future problems they are solving. You will develop and improve fundamental parallel algorithms and data structures. You will provide efficient solutions using GPUs through library development and direct application contributions.
  • Collaborating closely with the architecture, research, libraries, tools, and system software teams at NVIDIA to influence the build of next-generation architectures, software platforms, and programming models.
  • Engaging in deep optimization of high-performance operators, involving but not limited to GPU kernel optimization, instruction-level tuning, and compiler optimization. These optimizations will directly support customers to use NVIDIA libraries such as cuDNN, cuBLAS, and CUTLASS and Open- source libs like DeepGEMM, FlashMLA, FlashAttention, Flashinfer, etc.
  • Improving communication for Physical AI-related distributed transformer workloads by employing communication tools developed by NVIDIA. These include NCCL, NCCL GIN, and NVSHMEM, as well as open-source solutions like DeepEP and NCCL EP. This demands in-depth study of interconnect topologies (NVLINK) and network protocols (InfiniBand/RoCE) to develop efficient data transfer strategies alongside techniques enabling compute-communication overlap.


What we need to see:
  • BSc/MSc/PhD or equivalent experience in Computer Science, Electrical Engineering, Physics, Mathematics, or a related technical field.
  • 8+ years of hands-on validated ML/DL performance engineering experience with focus on improving GPU compute efficiency of training and inferencing workloads.
  • Experience with C, C++, or Python and proficiency with Linux.
  • Solid understanding of software development, programming techniques, and algorithms.
  • Strong mathematical fundamentals, including linear algebra and numerical methods.
  • Background in parallel programming and high-performance computing, with extensive knowledge of parallel architectures and methods for performance analysis and tuning. Experience in GPU programming is desirable.
  • Experience in distributed communication optimization is highly helpful. This involves familiarity with remote direct memory access, GPU interconnects, collective communication algorithms, and associated open-source libraries used in large-scale model training and inference.
  • Effective verbal/written communication, and technical presentation skills. Ability to communicate your ideas/code clearly through blog posts, GitHub, ppt.


Ways to stand out from the crowd:
  • Prior experience in writing CUDA kernels, and experience with Nsight System and Nsight Compute.
  • Experience in comprehensive evaluation and improvement of full-stack systems within at least one of these areas: LLM and HPC. Having expertise ranging from operator-level through framework-level to algorithm-level optimization is strongly preferred.
  • Proven software engineering fundamentals and system architecture thinking, with the ability to build modules and lead engineering approaches in complex systems.


Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until July 21, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

About NVIDIA Corporation

Nvidia, a global leader in graphics, gaming, and AI technology, offers Nvidia careers and internship opportunities for those passionate about driving innovation in the tech industry. you'll find a company committed to growth, teamwork, and leadership in computer science and machine learning domains.

About Nvidia

A Pioneer in Technology and Innovation

Nvidia has cemented its reputation as a powerhouse in developing advanced graphics processing units (GPUs) and has significantly contributed to the gaming industry's evolution. Moreover, its foray into AI and machine learning has opened new frontiers in technology, making Nvidia a beacon of innovation and a desirable workplace for ambitious tech professionals.

Job Opportunities

Diverse Positions in a Dynamic Field

Nvidia is continuously on the lookout for talented individuals across various domains, including hardware and software engineering, product design, marketing, and sales. Employment opportunities at Nvidia are vast, catering to a wide range of expertise and career aspirations.

Employment in Hardware and Graphics

For those fascinated by the intricacies of hardware and graphics technology, Nvidia offers positions that sit at the forefront of gaming and computing advancements.

Growth in Machine Learning and AI

Nvidia's leadership in AI and machine learning has created numerous vacancies for specialists eager to contribute to groundbreaking projects.

Recruitment in Computer Science

With the constant demand for innovation, Nvidia's recruitment efforts focus on computer science experts capable of pushing the boundaries of what's possible.

Internship Program

Opening Doors to Future Innovators

Nvidia's internship program is designed to nurture the next generation of technology leaders, offering hands-on experience in a culture that celebrates creativity and teamwork.

Benefits and Culture

Interns at Nvidia enjoy a plethora of benefits, from competitive stipends to mentorship opportunities, all within an environment that values growth and learning.

Opportunities for Students

Whether you're an undergraduate, a master's student, or a Ph.D. candidate, Nvidia's internships provide a real-world glimpse into the tech industry, offering valuable experience in various technology fields.

Pathways to Full-Time Employment

Many interns have transitioned into full-time positions, marking the start of successful careers at Nvidia. The internship program is more than a stepping stone into the company; it’s an investment in the professional development of interns. The goal is to ensure that interns are well-equipped for future challenges.

Nvidia Careers: More Than Just a Job

Nvidia offers more than just a job to its employees; it provides a front-row seat on the journey into the future of technology. Nvidia stands as a pillar of innovation with its vast opportunities in hardware, graphics, gaming, machine learning, and computer science. Nvidia careers serve as a launching pad for talented workers who aim to redefine the technological landscape. Whether through full-time positions or internships, joining Nvidia means contributing to a legacy of breakthroughs and becoming part of a global community dedicated to pushing the boundaries of what's possible.
Learn more about NVIDIA Corporation
Size
22,473 employees
Market Cap
$350.4 billion
Industry
Manufacturing & Automotive
Net Income
$4.3 billion
Founded
1993
5 Year Trend
+31.3%
Revenue
$16.6 billion
NASDAQ
NVDA
* Ladders Estimates

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