NVIDIA Logo

NVIDIA

Senior Deep Learning Performance Architect - LPU

Reposted 13 Days Ago
Be an Early Applicant
Remote or Hybrid
2 Locations
152K-288K Annually
Senior level
Remote or Hybrid
2 Locations
152K-288K Annually
Senior level
The role involves designing and optimizing GPU architectures for AI Inference, analyzing hardware-software relationships, and developing performance models.
The summary above was generated by AI

We are now looking for a Senior Deep Learning Performance Architect!

NVIDIA seeks a Senior DL Performance Architect to join our group of pioneers who enjoy pushing AI Inference performance boundaries. Our team focuses on ambitious hardware-software co-design to speed AI Inference workloads. This role gives an outstanding opportunity to develop world-class performance strategies, guide future GPU architecture decisions, and lead AI innovation. If you are passionate about AI efficiency Pareto curves, have a proven record of modeling LLM performance and architecting AI systems, and enjoy optimizing every cycle, this role may be perfect for you!

What you'll be doing:

  • Design novel GPU and system architectures to advance the forefront of AI Inference performance and efficiency

  • Construct, investigate, and test popular deep learning algorithms and applications

  • Understand and analyze the relationship between hardware and software architectures as it influences future algorithms and applications

  • Build efficient power and performance models of AI inference stack, while capturing minimal but significant information to guide next-gen HW architecture

  • Collaborate across the company to guide the direction of AI, working with software, research, and product teams

What we need to see:

  • A MS or PhD in a relevant field (CS, EE, Math) or equivalent experience, with 5+ years of relevant experience

  • Strong mathematical foundation in machine learning and deep learning

  • Expert programming skills in C, C++, and/or Python

  • Familiarity with GPU computing (CUDA or similar) and HPC (MPI, OpenMP) stack

  • Strong knowledge and coursework in computer architecture

Ways to stand out from the crowd:

  • Background with systems-level performance modeling, profiling, and analysis

  • Experience in characterizing and modeling system-level performance, accomplishing comparison studies, and documenting and publishing results

  • Background in improving AI Inference workloads by developing CUDA kernels or compilers for custom ASIC hardware

#LI-Hybrid

Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary ranges for this position are:
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.

Applications for this job will be accepted at least until November 3, 2026.

This posting is for an existing vacancy. 

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive 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.

Similar Jobs

An Hour Ago
Remote
United States
120K-190K Annually
Senior level
120K-190K Annually
Senior level
Artificial Intelligence • Legal Tech
Build GC AI’s technical sourcing program from the ground up. Partner with the CTO and hiring managers to define profiles, source senior engineering and AI talent, create talent maps and outreach sequences, manage candidates through virtual onsite handoff, track funnel metrics, and develop repeatable sourcing playbooks. The role requires strong technical fluency, especially in AI, advanced sourcing skills, and experience building recruiting infrastructure at a high-growth startup.
Top Skills: Ai AgentsAshby AtsBoolean SearchGitHugging FaceLinkedin RecruiterMachine Learning InferenceMetaviewRagX
An Hour Ago
Easy Apply
Remote
United States
Easy Apply
95K-110K Annually
Junior
95K-110K Annually
Junior
Healthtech • Software
Own end-to-end quality for FHIR-based APIs and clinical workflows. Plan and execute manual and automated testing, validate healthcare data schemas and integrations, document defects, analyze results, and improve QA processes. Collaborate with engineering, product, implementation, and solution architecture teams while communicating findings to technical and external client stakeholders.
Top Skills: FhirHl7Restful Apis
An Hour Ago
Remote or Hybrid
US
95K-115K Annually
Senior level
95K-115K Annually
Senior level
AdTech • Consumer Web • Digital Media • eCommerce • Marketing Tech
Own and scale the direct-to-consumer e-commerce channel, including acquisition, conversion, CRM, lifecycle marketing, promotions, merchandising, retention, analytics, and profitability. Manage agencies, vendors, and technology partners while collaborating across brand, operations, finance, sales, and editorial teams. Develop performance reporting, testing roadmaps, inventory and fulfillment partnerships, and marketplace expansion strategies.
Top Skills: Shopify

What you need to know about the NYC Tech Scene

As the undisputed financial capital of the world, New York City is an epicenter of startup funding activity. The city has a thriving fintech scene and is a major player in verticals ranging from AI to biotech, cybersecurity and digital media. It also has universities like NYU, Columbia and Cornell Tech attracting students and researchers from across the globe, providing the ecosystem with a constant influx of world-class talent. And its East Coast location and three international airports make it a perfect spot for European companies establishing a foothold in the United States.

Key Facts About NYC Tech

  • Number of Tech Workers: 549,200; 6% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Capgemini, Bloomberg, IBM, Spotify
  • Key Industries: Artificial intelligence, Fintech
  • Funding Landscape: $25.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Greycroft, Thrive Capital, Union Square Ventures, FirstMark Capital, Tiger Global Management, Tribeca Venture Partners, Insight Partners, Two Sigma Ventures
  • Research Centers and Universities: Columbia University, New York University, Fordham University, CUNY, AI Now Institute, Flatiron Institute, C.N. Yang Institute for Theoretical Physics, NASA Space Radiation Laboratory

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account