Role at a glance
- Salary
- $152K – $287.5K/yr
- Location
- 3 Locations, California, United States
- Work arrangement
- On-site
- Employment
- Full-time
- Experience
- 3+ years of hands-on experience in system evaluation of AI/ML workloads or performance analysis, modeling and optimizations for AI.
- Education
- A minimum qualification of a Master's degree (or equivalent experience) in Computer Science, Electrical Engineering or related fields.
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Role Summary
The Senior Performance Architect will shape the performance of NVIDIA’s Nemotron models through analytical performance modeling, analysis, and forward projections. The role supports model–system–hardware co-design by evaluating deployment efficiency and partnering with research, framework, compiler, and hardware teams on Generative AI systems.
What You'll Do
- Develop high-fidelity analytical performance models for emerging algorithmic techniques and hardware optimizations.
- Prioritize features and guide future software and hardware roadmaps using performance modeling and analysis.
- Model the end-to-end performance impact of GenAI workflows such as Speculative Decoding, Agentic Pipelines, inference-time compute...
- Define metrics, design experiments, and visualize large performance datasets to identify resource bottlenecks.
- Collaborate with deep learning researchers, hardware architects, and software engineers.
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View full postingQualifications
Master's degree or equivalent experience in Computer Science, Electrical Engineering, or a related field; background in computer architecture, roofline modeling, queuing theory, and statistical performance analysis; understanding of ML fundamentals, model parallelism, and inference serving; proficiency in Python and optionally C++; 3+ years of AI/ML workload evaluation or AI performance analysis, modeling, and optimization; experience defining metrics, designing experiments, visualizing large performance datasets, and using deep learning frameworks including PyTorch, TRT-LLM, VLLM, and SGLang.
Required
- Proven track record of working in multi-functional teams spanning algorithms, software, and hardware architecture.
- Ability to distill complex analyses into clear recommendations for technical and non-technical collaborators.
- Experience with GPU computing (CUDA).
Preferred
- Proven track record of working in multi-functional teams spanning algorithms, software, and hardware architecture.
- Ability to distill complex analyses into clear recommendations for technical and non-technical collaborators.
- Experience with GPU computing (CUDA).
Original job description
Content provided by the employer
Original job description
Content provided by the employer
We are now looking for a Senior Performance Architect for Nemotron! At NVIDIA, we are redefining the future of AI systems through deep model–system–hardware co-design. We are looking for a forward-thinking Nemotron Performance Architect to shape the next generation of Nemotron models through performance modeling, analysis, and forward projections. In this role, you will predict before we build - developing high-fidelity models to evaluate how architectural choices translate into real-world deployment efficiency. You will ensure that future models achieve Pareto-optimal trade-offs across accuracy, throughput, and interactivity on target platforms.
Recent efforts such as LatentMoE architectures and the Nemotron Super model exemplify the kind of performance-driven co-design you will help advance—where modeling insights directly shape model architecture and system efficiency at scale. This role sits at the center of Generative AI evolution, partnering across research, framework development, compiler, and hardware teams to guide decisions that determine how efficiently intelligence scales in production.
What You’ll Be Doing:
Develop high-fidelity analytical performance models to prototype emerging algorithmic techniques & hardware optimizations to drive model-hardware co-design Nemotron family of models.
Prioritize features to guide future software and hardware roadmap based on detailed performance modeling and analysis
Model end-to-end performance impact of emerging GenAI workflows - such as Speculative Decoding, Agentic Pipelines, Inference-time compute scaling, RL etc. – to understand future datacenter needs
This position requires you to keep up with the latest DL research and collaborate with diverse teams, including DL researchers, hardware architects, and software engineers.
What we need to see:
A minimum qualification of a Master's degree (or equivalent experience) in Computer Science, Electrical Engineering or related fields.
Strong background in computer architecture, roofline modeling, queuing theory and statistical performance analysis techniques.
Solid understanding of ML fundamentals, model parallelism and inference serving techniques.
Proficiency in Python (and optionally C++) for simulator design and data analysis.
3+ years of hands-on experience in system evaluation of AI/ML workloads or performance analysis, modeling and optimizations for AI.
Comfortable defining metrics, designing experiments and visualizing large performance datasets to identify resource bottlenecks.
Experience with deep learning frameworks like PyTorch, TRT-LLM, VLLM, SGLang
A Growth mindset and pragmatic “measure, iterate, deliver” approach.
Ways to Stand Out from the Crowd
Proven track record of working in multi-functional teams, spanning algorithms, software and hardware architecture.
Ability to distill complex analyses into clear recommendations for both technical and non-technical collaborators.
Experience with GPU computing (CUDA)
You will also be eligible for equity and benefits.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.About the company
NVIDIA
Large Enterprise
NVIDIA is a leading technology company renowned for its graphics processing units (GPUs) and innovative computing solutions that enhance visual experiences across multiple platforms, including gaming, scientific research, and artificial intelligence. Founded in 1993, the company has expanded its offerings to include powerful AI frameworks and deep learning platforms, making significant contributions to industries such as gaming, data centers, automotive, and healthcare. NVIDIA's commitment to pushing the boundaries of visual computing continues to drive advancements in both hardware and software, positioning the company at the forefront of emerging technologies and digital transformation.
NVIDIA is a leading technology company renowned for its graphics processing units (GPUs) and innovative computing solutions that enhance visual experiences across multiple platforms, including gaming, scientific research, and artificial intelligence. Founded in 1993, the company has expanded its offerings to include powerful AI frameworks and deep learning platforms, making significant contributions to industries such as gaming, data centers, automotive, and healthcare. NVIDIA's commitment to pushing the boundaries of visual computing continues to drive advancements in both hardware and software, positioning the company at the forefront of emerging technologies and digital transformation.